Analysis of 111/999 NHS calls and 111 online reports
Quentin Leclerc, Emily Nightingale, Samuel Abbott & Thibaut Jombart, for CMMID
Thursday 04 March 2021
1 Data preparation
1.1 Outline
Load scripts: loads libraries and useful scripts used in the analyses; all
.Rfiles contained inscriptsat the root of the factory are automatically loadedLoad data: imports datasets, and may contain some ad hoc changes to the data such as specific data cleaning (not used in other reports), new variables used in the analyses, etc.
1.2 Load packages
library(reportfactory)
library(here)
library(rio)
library(tidyverse)
library(incidence)
library(distcrete)
library(epitrix)
library(earlyR)
library(projections)
library(linelist)
library(remotes)
library(janitor)
library(kableExtra)
library(DT)
library(cyphr)
library(chngpt)
library(lubridate)
library(ggpubr)
library(ggnewscale)1.3 Load scripts
These scripts will load:
- all scripts stored as
.Rfiles inside/scripts/ - all scripts stored as
.Rfiles inside/src/
These scripts also contain routines to access the latest clean encrypted data (see next section).
1.4 Load clean data
We import the latest NHS pathways data:
x <- import_pathways() %>%
as_tibble()
x
## # A tibble: 455,080 x 11
## site_type date sex age ccg_code ccg_name count postcode nhs_region
## <chr> <date> <chr> <chr> <chr> <chr> <int> <chr> <chr>
## 1 111 2020-03-18 female miss… e380000… nhs_glo… 1 gl34fe South West
## 2 111 2020-03-18 female miss… e380001… nhs_sou… 1 ne325nn North Eas…
## 3 111 2020-03-18 female 0-18 e380000… nhs_air… 8 bd57jr North Eas…
## 4 111 2020-03-18 female 0-18 e380000… nhs_ash… 7 tn254ab South East
## 5 111 2020-03-18 female 0-18 e380000… nhs_bar… 35 rm13ae London
## 6 111 2020-03-18 female 0-18 e380000… nhs_bar… 9 n111np London
## 7 111 2020-03-18 female 0-18 e380000… nhs_bar… 11 s752py North Eas…
## 8 111 2020-03-18 female 0-18 e380000… nhs_bas… 19 ss143hg East of E…
## 9 111 2020-03-18 female 0-18 e380000… nhs_bas… 6 dn227xf North Eas…
## 10 111 2020-03-18 female 0-18 e380000… nhs_bat… 9 ba25rp South West
## # … with 455,070 more rows, and 2 more variables: day <int>, weekday <fct>We also import demographics data for NHS regions in England, used later in our analysis:
path <- here::here("data", "csv", "nhs_region_population_2018.csv")
nhs_region_pop <- rio::import(path) %>%
mutate(nhs_region = str_to_title(gsub("_"," ",nhs_region)))
nhs_region_pop$nhs_region <- gsub(" Of ", " of ", nhs_region_pop$nhs_region)
nhs_region_pop$nhs_region <- gsub(" And ", " and ", nhs_region_pop$nhs_region)
nhs_region_pop
## nhs_region variable value
## 1 North West 0-18 0.22538599
## 2 North East and Yorkshire 0-18 0.21876449
## 3 Midlands 0-18 0.22564656
## 4 East of England 0-18 0.22810783
## 5 London 0-18 0.23764782
## 6 South East 0-18 0.22458811
## 7 South West 0-18 0.20799797
## 8 North West 19-69 0.64274078
## 9 North East and Yorkshire 19-69 0.64437753
## 10 Midlands 19-69 0.63876675
## 11 East of England 19-69 0.63034229
## 12 London 19-69 0.67820084
## 13 South East 19-69 0.63267336
## 14 South West 19-69 0.63176131
## 15 North West 70-120 0.13187323
## 16 North East and Yorkshire 70-120 0.13685797
## 17 Midlands 70-120 0.13558669
## 18 East of England 70-120 0.14154988
## 19 London 70-120 0.08415135
## 20 South East 70-120 0.14273853
## 21 South West 70-120 0.16024072Finally, we import publically available deaths per NHS region:
dth <- import_deaths() %>%
mutate(nhs_region = str_to_title(gsub("_"," ",nhs_region)))
#truncation to account for reporting delay
delay_max <- 21
dth$nhs_region <- gsub(" Of ", " of ", dth$nhs_region)
dth$nhs_region <- gsub(" And ", " and ", dth$nhs_region)
dth
## date_report nhs_region deaths
## 1 2020-03-01 East of England 0
## 2 2020-03-02 East of England 1
## 3 2020-03-03 East of England 0
## 4 2020-03-04 East of England 0
## 5 2020-03-05 East of England 0
## 6 2020-03-06 East of England 1
## 7 2020-03-07 East of England 0
## 8 2020-03-08 East of England 0
## 9 2020-03-09 East of England 1
## 10 2020-03-10 East of England 0
## 11 2020-03-11 East of England 0
## 12 2020-03-12 East of England 0
## 13 2020-03-13 East of England 1
## 14 2020-03-14 East of England 2
## 15 2020-03-15 East of England 2
## 16 2020-03-16 East of England 1
## 17 2020-03-17 East of England 1
## 18 2020-03-18 East of England 5
## 19 2020-03-19 East of England 4
## 20 2020-03-20 East of England 2
## 21 2020-03-21 East of England 11
## 22 2020-03-22 East of England 12
## 23 2020-03-23 East of England 11
## 24 2020-03-24 East of England 19
## 25 2020-03-25 East of England 26
## 26 2020-03-26 East of England 36
## 27 2020-03-27 East of England 38
## 28 2020-03-28 East of England 28
## 29 2020-03-29 East of England 43
## 30 2020-03-30 East of England 45
## 31 2020-03-31 East of England 70
## 32 2020-04-01 East of England 63
## 33 2020-04-02 East of England 65
## 34 2020-04-03 East of England 80
## 35 2020-04-04 East of England 71
## 36 2020-04-05 East of England 76
## 37 2020-04-06 East of England 71
## 38 2020-04-07 East of England 93
## 39 2020-04-08 East of England 111
## 40 2020-04-09 East of England 87
## 41 2020-04-10 East of England 74
## 42 2020-04-11 East of England 92
## 43 2020-04-12 East of England 100
## 44 2020-04-13 East of England 78
## 45 2020-04-14 East of England 61
## 46 2020-04-15 East of England 82
## 47 2020-04-16 East of England 74
## 48 2020-04-17 East of England 86
## 49 2020-04-18 East of England 64
## 50 2020-04-19 East of England 67
## 51 2020-04-20 East of England 67
## 52 2020-04-21 East of England 75
## 53 2020-04-22 East of England 67
## 54 2020-04-23 East of England 49
## 55 2020-04-24 East of England 66
## 56 2020-04-25 East of England 54
## 57 2020-04-26 East of England 48
## 58 2020-04-27 East of England 46
## 59 2020-04-28 East of England 58
## 60 2020-04-29 East of England 32
## 61 2020-04-30 East of England 45
## 62 2020-05-01 East of England 49
## 63 2020-05-02 East of England 29
## 64 2020-05-03 East of England 41
## 65 2020-05-04 East of England 19
## 66 2020-05-05 East of England 36
## 67 2020-05-06 East of England 31
## 68 2020-05-07 East of England 33
## 69 2020-05-08 East of England 33
## 70 2020-05-09 East of England 29
## 71 2020-05-10 East of England 22
## 72 2020-05-11 East of England 18
## 73 2020-05-12 East of England 21
## 74 2020-05-13 East of England 27
## 75 2020-05-14 East of England 26
## 76 2020-05-15 East of England 19
## 77 2020-05-16 East of England 26
## 78 2020-05-17 East of England 17
## 79 2020-05-18 East of England 25
## 80 2020-05-19 East of England 15
## 81 2020-05-20 East of England 26
## 82 2020-05-21 East of England 21
## 83 2020-05-22 East of England 13
## 84 2020-05-23 East of England 12
## 85 2020-05-24 East of England 17
## 86 2020-05-25 East of England 25
## 87 2020-05-26 East of England 14
## 88 2020-05-27 East of England 12
## 89 2020-05-28 East of England 17
## 90 2020-05-29 East of England 16
## 91 2020-05-30 East of England 9
## 92 2020-05-31 East of England 8
## 93 2020-06-01 East of England 17
## 94 2020-06-02 East of England 14
## 95 2020-06-03 East of England 10
## 96 2020-06-04 East of England 7
## 97 2020-06-05 East of England 14
## 98 2020-06-06 East of England 5
## 99 2020-06-07 East of England 9
## 100 2020-06-08 East of England 7
## 101 2020-06-09 East of England 6
## 102 2020-06-10 East of England 8
## 103 2020-06-11 East of England 1
## 104 2020-06-12 East of England 9
## 105 2020-06-13 East of England 5
## 106 2020-06-14 East of England 4
## 107 2020-06-15 East of England 8
## 108 2020-06-16 East of England 3
## 109 2020-06-17 East of England 7
## 110 2020-06-18 East of England 4
## 111 2020-06-19 East of England 7
## 112 2020-06-20 East of England 4
## 113 2020-06-21 East of England 3
## 114 2020-06-22 East of England 6
## 115 2020-06-23 East of England 5
## 116 2020-06-24 East of England 4
## 117 2020-06-25 East of England 1
## 118 2020-06-26 East of England 5
## 119 2020-06-27 East of England 6
## 120 2020-06-28 East of England 8
## 121 2020-06-29 East of England 4
## 122 2020-06-30 East of England 5
## 123 2020-07-01 East of England 2
## 124 2020-07-02 East of England 5
## 125 2020-07-03 East of England 0
## 126 2020-07-04 East of England 3
## 127 2020-07-05 East of England 1
## 128 2020-07-06 East of England 2
## 129 2020-07-07 East of England 2
## 130 2020-07-08 East of England 0
## 131 2020-07-09 East of England 8
## 132 2020-07-10 East of England 4
## 133 2020-07-11 East of England 2
## 134 2020-07-12 East of England 1
## 135 2020-07-13 East of England 8
## 136 2020-07-14 East of England 2
## 137 2020-07-15 East of England 0
## 138 2020-07-16 East of England 0
## 139 2020-07-17 East of England 0
## 140 2020-07-18 East of England 0
## 141 2020-07-19 East of England 1
## 142 2020-07-20 East of England 1
## 143 2020-07-21 East of England 1
## 144 2020-07-22 East of England 2
## 145 2020-07-23 East of England 1
## 146 2020-07-24 East of England 1
## 147 2020-07-25 East of England 0
## 148 2020-07-26 East of England 1
## 149 2020-07-27 East of England 1
## 150 2020-07-28 East of England 2
## 151 2020-07-29 East of England 0
## 152 2020-07-30 East of England 0
## 153 2020-07-31 East of England 1
## 154 2020-08-01 East of England 0
## 155 2020-08-02 East of England 0
## 156 2020-08-03 East of England 0
## 157 2020-08-04 East of England 1
## 158 2020-08-05 East of England 1
## 159 2020-08-06 East of England 0
## 160 2020-08-07 East of England 1
## 161 2020-08-08 East of England 0
## 162 2020-08-09 East of England 0
## 163 2020-08-10 East of England 1
## 164 2020-08-11 East of England 2
## 165 2020-08-12 East of England 1
## 166 2020-08-13 East of England 0
## 167 2020-08-14 East of England 1
## 168 2020-08-15 East of England 1
## 169 2020-08-16 East of England 0
## 170 2020-08-17 East of England 0
## 171 2020-08-18 East of England 2
## 172 2020-08-19 East of England 1
## 173 2020-08-20 East of England 1
## 174 2020-08-21 East of England 0
## 175 2020-08-22 East of England 1
## 176 2020-08-23 East of England 1
## 177 2020-08-24 East of England 0
## 178 2020-08-25 East of England 0
## 179 2020-08-26 East of England 1
## 180 2020-08-27 East of England 1
## 181 2020-08-28 East of England 0
## 182 2020-08-29 East of England 0
## 183 2020-08-30 East of England 0
## 184 2020-08-31 East of England 0
## 185 2020-09-01 East of England 0
## 186 2020-09-02 East of England 0
## 187 2020-09-03 East of England 1
## 188 2020-09-04 East of England 1
## 189 2020-09-05 East of England 0
## 190 2020-09-06 East of England 1
## 191 2020-09-07 East of England 0
## 192 2020-09-08 East of England 0
## 193 2020-09-09 East of England 0
## 194 2020-09-10 East of England 0
## 195 2020-09-11 East of England 0
## 196 2020-09-12 East of England 0
## 197 2020-09-13 East of England 1
## 198 2020-09-14 East of England 1
## 199 2020-09-15 East of England 0
## 200 2020-09-16 East of England 0
## 201 2020-09-17 East of England 0
## 202 2020-09-18 East of England 0
## 203 2020-09-19 East of England 0
## 204 2020-09-20 East of England 2
## 205 2020-09-21 East of England 0
## 206 2020-09-22 East of England 2
## 207 2020-09-23 East of England 1
## 208 2020-09-24 East of England 0
## 209 2020-09-25 East of England 1
## 210 2020-09-26 East of England 1
## 211 2020-09-27 East of England 1
## 212 2020-09-28 East of England 2
## 213 2020-09-29 East of England 2
## 214 2020-09-30 East of England 2
## 215 2020-10-01 East of England 2
## 216 2020-10-02 East of England 1
## 217 2020-10-03 East of England 1
## 218 2020-10-04 East of England 0
## 219 2020-10-05 East of England 0
## 220 2020-10-06 East of England 4
## 221 2020-10-07 East of England 6
## 222 2020-10-08 East of England 3
## 223 2020-10-09 East of England 1
## 224 2020-10-10 East of England 6
## 225 2020-10-11 East of England 2
## 226 2020-10-12 East of England 2
## 227 2020-10-13 East of England 1
## 228 2020-10-14 East of England 3
## 229 2020-10-15 East of England 4
## 230 2020-10-16 East of England 5
## 231 2020-10-17 East of England 6
## 232 2020-10-18 East of England 7
## 233 2020-10-19 East of England 5
## 234 2020-10-20 East of England 9
## 235 2020-10-21 East of England 8
## 236 2020-10-22 East of England 7
## 237 2020-10-23 East of England 14
## 238 2020-10-24 East of England 1
## 239 2020-10-25 East of England 10
## 240 2020-10-26 East of England 10
## 241 2020-10-27 East of England 8
## 242 2020-10-28 East of England 12
## 243 2020-10-29 East of England 10
## 244 2020-10-30 East of England 12
## 245 2020-10-31 East of England 15
## 246 2020-11-01 East of England 14
## 247 2020-11-02 East of England 9
## 248 2020-11-03 East of England 14
## 249 2020-11-04 East of England 11
## 250 2020-11-05 East of England 12
## 251 2020-11-06 East of England 18
## 252 2020-11-07 East of England 10
## 253 2020-11-08 East of England 13
## 254 2020-11-09 East of England 16
## 255 2020-11-10 East of England 26
## 256 2020-11-11 East of England 14
## 257 2020-11-12 East of England 14
## 258 2020-11-13 East of England 21
## 259 2020-11-14 East of England 19
## 260 2020-11-15 East of England 13
## 261 2020-11-16 East of England 11
## 262 2020-11-17 East of England 17
## 263 2020-11-18 East of England 19
## 264 2020-11-19 East of England 23
## 265 2020-11-20 East of England 24
## 266 2020-11-21 East of England 19
## 267 2020-11-22 East of England 21
## 268 2020-11-23 East of England 18
## 269 2020-11-24 East of England 21
## 270 2020-11-25 East of England 19
## 271 2020-11-26 East of England 19
## 272 2020-11-27 East of England 14
## 273 2020-11-28 East of England 28
## 274 2020-11-29 East of England 19
## 275 2020-11-30 East of England 22
## 276 2020-12-01 East of England 26
## 277 2020-12-02 East of England 18
## 278 2020-12-03 East of England 24
## 279 2020-12-04 East of England 25
## 280 2020-12-05 East of England 25
## 281 2020-12-06 East of England 21
## 282 2020-12-07 East of England 16
## 283 2020-12-08 East of England 26
## 284 2020-12-09 East of England 20
## 285 2020-12-10 East of England 32
## 286 2020-12-11 East of England 32
## 287 2020-12-12 East of England 27
## 288 2020-12-13 East of England 25
## 289 2020-12-14 East of England 32
## 290 2020-12-15 East of England 35
## 291 2020-12-16 East of England 29
## 292 2020-12-17 East of England 42
## 293 2020-12-18 East of England 44
## 294 2020-12-19 East of England 54
## 295 2020-12-20 East of England 52
## 296 2020-12-21 East of England 66
## 297 2020-12-22 East of England 52
## 298 2020-12-23 East of England 62
## 299 2020-12-24 East of England 61
## 300 2020-12-25 East of England 58
## 301 2020-12-26 East of England 64
## 302 2020-12-27 East of England 54
## 303 2020-12-28 East of England 71
## 304 2020-12-29 East of England 54
## 305 2020-12-30 East of England 76
## 306 2020-12-31 East of England 82
## 307 2021-01-01 East of England 89
## 308 2021-01-02 East of England 66
## 309 2021-01-03 East of England 78
## 310 2021-01-04 East of England 87
## 311 2021-01-05 East of England 102
## 312 2021-01-06 East of England 100
## 313 2021-01-07 East of England 116
## 314 2021-01-08 East of England 96
## 315 2021-01-09 East of England 133
## 316 2021-01-10 East of England 125
## 317 2021-01-11 East of England 126
## 318 2021-01-12 East of England 131
## 319 2021-01-13 East of England 131
## 320 2021-01-14 East of England 126
## 321 2021-01-15 East of England 118
## 322 2021-01-16 East of England 131
## 323 2021-01-17 East of England 133
## 324 2021-01-18 East of England 120
## 325 2021-01-19 East of England 129
## 326 2021-01-20 East of England 147
## 327 2021-01-21 East of England 134
## 328 2021-01-22 East of England 122
## 329 2021-01-23 East of England 102
## 330 2021-01-24 East of England 101
## 331 2021-01-25 East of England 112
## 332 2021-01-26 East of England 89
## 333 2021-01-27 East of England 94
## 334 2021-01-28 East of England 110
## 335 2021-01-29 East of England 95
## 336 2021-01-30 East of England 85
## 337 2021-01-31 East of England 73
## 338 2021-02-01 East of England 65
## 339 2021-02-02 East of England 73
## 340 2021-02-03 East of England 82
## 341 2021-02-04 East of England 75
## 342 2021-02-05 East of England 66
## 343 2021-02-06 East of England 77
## 344 2021-02-07 East of England 62
## 345 2021-02-08 East of England 73
## 346 2021-02-09 East of England 62
## 347 2021-02-10 East of England 52
## 348 2021-02-11 East of England 52
## 349 2021-02-12 East of England 47
## 350 2021-02-13 East of England 47
## 351 2021-02-14 East of England 32
## 352 2021-02-15 East of England 48
## 353 2021-02-16 East of England 45
## 354 2021-02-17 East of England 46
## 355 2021-02-18 East of England 29
## 356 2021-02-19 East of England 28
## 357 2021-02-20 East of England 30
## 358 2021-02-21 East of England 24
## 359 2021-02-22 East of England 26
## 360 2021-02-23 East of England 27
## 361 2021-02-24 East of England 17
## 362 2021-02-25 East of England 23
## 363 2021-02-26 East of England 13
## 364 2021-02-27 East of England 21
## 365 2021-02-28 East of England 14
## 366 2021-03-01 East of England 11
## 367 2021-03-02 East of England 2
## 368 2020-03-01 London 0
## 369 2020-03-02 London 0
## 370 2020-03-03 London 0
## 371 2020-03-04 London 0
## 372 2020-03-05 London 0
## 373 2020-03-06 London 1
## 374 2020-03-07 London 0
## 375 2020-03-08 London 0
## 376 2020-03-09 London 1
## 377 2020-03-10 London 0
## 378 2020-03-11 London 5
## 379 2020-03-12 London 6
## 380 2020-03-13 London 10
## 381 2020-03-14 London 13
## 382 2020-03-15 London 9
## 383 2020-03-16 London 15
## 384 2020-03-17 London 23
## 385 2020-03-18 London 28
## 386 2020-03-19 London 25
## 387 2020-03-20 London 44
## 388 2020-03-21 London 49
## 389 2020-03-22 London 54
## 390 2020-03-23 London 63
## 391 2020-03-24 London 86
## 392 2020-03-25 London 112
## 393 2020-03-26 London 130
## 394 2020-03-27 London 130
## 395 2020-03-28 London 123
## 396 2020-03-29 London 145
## 397 2020-03-30 London 151
## 398 2020-03-31 London 183
## 399 2020-04-01 London 202
## 400 2020-04-02 London 191
## 401 2020-04-03 London 199
## 402 2020-04-04 London 231
## 403 2020-04-05 London 195
## 404 2020-04-06 London 198
## 405 2020-04-07 London 220
## 406 2020-04-08 London 239
## 407 2020-04-09 London 207
## 408 2020-04-10 London 171
## 409 2020-04-11 London 178
## 410 2020-04-12 London 159
## 411 2020-04-13 London 166
## 412 2020-04-14 London 143
## 413 2020-04-15 London 143
## 414 2020-04-16 London 140
## 415 2020-04-17 London 101
## 416 2020-04-18 London 101
## 417 2020-04-19 London 104
## 418 2020-04-20 London 96
## 419 2020-04-21 London 96
## 420 2020-04-22 London 109
## 421 2020-04-23 London 77
## 422 2020-04-24 London 71
## 423 2020-04-25 London 58
## 424 2020-04-26 London 53
## 425 2020-04-27 London 52
## 426 2020-04-28 London 44
## 427 2020-04-29 London 45
## 428 2020-04-30 London 40
## 429 2020-05-01 London 41
## 430 2020-05-02 London 41
## 431 2020-05-03 London 36
## 432 2020-05-04 London 30
## 433 2020-05-05 London 25
## 434 2020-05-06 London 37
## 435 2020-05-07 London 37
## 436 2020-05-08 London 31
## 437 2020-05-09 London 23
## 438 2020-05-10 London 26
## 439 2020-05-11 London 18
## 440 2020-05-12 London 18
## 441 2020-05-13 London 17
## 442 2020-05-14 London 20
## 443 2020-05-15 London 19
## 444 2020-05-16 London 14
## 445 2020-05-17 London 16
## 446 2020-05-18 London 11
## 447 2020-05-19 London 14
## 448 2020-05-20 London 19
## 449 2020-05-21 London 12
## 450 2020-05-22 London 10
## 451 2020-05-23 London 6
## 452 2020-05-24 London 7
## 453 2020-05-25 London 9
## 454 2020-05-26 London 14
## 455 2020-05-27 London 7
## 456 2020-05-28 London 8
## 457 2020-05-29 London 7
## 458 2020-05-30 London 12
## 459 2020-05-31 London 6
## 460 2020-06-01 London 10
## 461 2020-06-02 London 8
## 462 2020-06-03 London 6
## 463 2020-06-04 London 8
## 464 2020-06-05 London 4
## 465 2020-06-06 London 0
## 466 2020-06-07 London 5
## 467 2020-06-08 London 5
## 468 2020-06-09 London 5
## 469 2020-06-10 London 8
## 470 2020-06-11 London 5
## 471 2020-06-12 London 3
## 472 2020-06-13 London 3
## 473 2020-06-14 London 3
## 474 2020-06-15 London 1
## 475 2020-06-16 London 2
## 476 2020-06-17 London 1
## 477 2020-06-18 London 2
## 478 2020-06-19 London 5
## 479 2020-06-20 London 3
## 480 2020-06-21 London 4
## 481 2020-06-22 London 2
## 482 2020-06-23 London 1
## 483 2020-06-24 London 4
## 484 2020-06-25 London 3
## 485 2020-06-26 London 2
## 486 2020-06-27 London 1
## 487 2020-06-28 London 2
## 488 2020-06-29 London 2
## 489 2020-06-30 London 1
## 490 2020-07-01 London 3
## 491 2020-07-02 London 2
## 492 2020-07-03 London 2
## 493 2020-07-04 London 1
## 494 2020-07-05 London 3
## 495 2020-07-06 London 2
## 496 2020-07-07 London 1
## 497 2020-07-08 London 3
## 498 2020-07-09 London 4
## 499 2020-07-10 London 0
## 500 2020-07-11 London 1
## 501 2020-07-12 London 1
## 502 2020-07-13 London 1
## 503 2020-07-14 London 0
## 504 2020-07-15 London 2
## 505 2020-07-16 London 0
## 506 2020-07-17 London 0
## 507 2020-07-18 London 2
## 508 2020-07-19 London 0
## 509 2020-07-20 London 0
## 510 2020-07-21 London 1
## 511 2020-07-22 London 0
## 512 2020-07-23 London 2
## 513 2020-07-24 London 0
## 514 2020-07-25 London 1
## 515 2020-07-26 London 0
## 516 2020-07-27 London 1
## 517 2020-07-28 London 0
## 518 2020-07-29 London 0
## 519 2020-07-30 London 1
## 520 2020-07-31 London 0
## 521 2020-08-01 London 0
## 522 2020-08-02 London 3
## 523 2020-08-03 London 0
## 524 2020-08-04 London 0
## 525 2020-08-05 London 0
## 526 2020-08-06 London 1
## 527 2020-08-07 London 0
## 528 2020-08-08 London 0
## 529 2020-08-09 London 0
## 530 2020-08-10 London 0
## 531 2020-08-11 London 1
## 532 2020-08-12 London 0
## 533 2020-08-13 London 2
## 534 2020-08-14 London 0
## 535 2020-08-15 London 0
## 536 2020-08-16 London 0
## 537 2020-08-17 London 1
## 538 2020-08-18 London 1
## 539 2020-08-19 London 0
## 540 2020-08-20 London 1
## 541 2020-08-21 London 0
## 542 2020-08-22 London 0
## 543 2020-08-23 London 0
## 544 2020-08-24 London 1
## 545 2020-08-25 London 1
## 546 2020-08-26 London 0
## 547 2020-08-27 London 0
## 548 2020-08-28 London 0
## 549 2020-08-29 London 0
## 550 2020-08-30 London 0
## 551 2020-08-31 London 1
## 552 2020-09-01 London 0
## 553 2020-09-02 London 1
## 554 2020-09-03 London 1
## 555 2020-09-04 London 0
## 556 2020-09-05 London 0
## 557 2020-09-06 London 2
## 558 2020-09-07 London 0
## 559 2020-09-08 London 0
## 560 2020-09-09 London 0
## 561 2020-09-10 London 2
## 562 2020-09-11 London 1
## 563 2020-09-12 London 1
## 564 2020-09-13 London 0
## 565 2020-09-14 London 0
## 566 2020-09-15 London 1
## 567 2020-09-16 London 2
## 568 2020-09-17 London 2
## 569 2020-09-18 London 1
## 570 2020-09-19 London 3
## 571 2020-09-20 London 3
## 572 2020-09-21 London 2
## 573 2020-09-22 London 6
## 574 2020-09-23 London 4
## 575 2020-09-24 London 3
## 576 2020-09-25 London 1
## 577 2020-09-26 London 1
## 578 2020-09-27 London 1
## 579 2020-09-28 London 3
## 580 2020-09-29 London 7
## 581 2020-09-30 London 6
## 582 2020-10-01 London 4
## 583 2020-10-02 London 1
## 584 2020-10-03 London 3
## 585 2020-10-04 London 2
## 586 2020-10-05 London 7
## 587 2020-10-06 London 4
## 588 2020-10-07 London 6
## 589 2020-10-08 London 6
## 590 2020-10-09 London 7
## 591 2020-10-10 London 3
## 592 2020-10-11 London 5
## 593 2020-10-12 London 7
## 594 2020-10-13 London 4
## 595 2020-10-14 London 6
## 596 2020-10-15 London 13
## 597 2020-10-16 London 6
## 598 2020-10-17 London 2
## 599 2020-10-18 London 5
## 600 2020-10-19 London 11
## 601 2020-10-20 London 8
## 602 2020-10-21 London 14
## 603 2020-10-22 London 12
## 604 2020-10-23 London 7
## 605 2020-10-24 London 18
## 606 2020-10-25 London 10
## 607 2020-10-26 London 10
## 608 2020-10-27 London 12
## 609 2020-10-28 London 23
## 610 2020-10-29 London 14
## 611 2020-10-30 London 17
## 612 2020-10-31 London 7
## 613 2020-11-01 London 17
## 614 2020-11-02 London 16
## 615 2020-11-03 London 10
## 616 2020-11-04 London 18
## 617 2020-11-05 London 17
## 618 2020-11-06 London 12
## 619 2020-11-07 London 21
## 620 2020-11-08 London 15
## 621 2020-11-09 London 28
## 622 2020-11-10 London 14
## 623 2020-11-11 London 15
## 624 2020-11-12 London 16
## 625 2020-11-13 London 14
## 626 2020-11-14 London 21
## 627 2020-11-15 London 18
## 628 2020-11-16 London 29
## 629 2020-11-17 London 29
## 630 2020-11-18 London 23
## 631 2020-11-19 London 24
## 632 2020-11-20 London 20
## 633 2020-11-21 London 19
## 634 2020-11-22 London 29
## 635 2020-11-23 London 19
## 636 2020-11-24 London 27
## 637 2020-11-25 London 30
## 638 2020-11-26 London 25
## 639 2020-11-27 London 28
## 640 2020-11-28 London 23
## 641 2020-11-29 London 40
## 642 2020-11-30 London 19
## 643 2020-12-01 London 28
## 644 2020-12-02 London 30
## 645 2020-12-03 London 27
## 646 2020-12-04 London 30
## 647 2020-12-05 London 26
## 648 2020-12-06 London 25
## 649 2020-12-07 London 29
## 650 2020-12-08 London 35
## 651 2020-12-09 London 28
## 652 2020-12-10 London 31
## 653 2020-12-11 London 27
## 654 2020-12-12 London 33
## 655 2020-12-13 London 33
## 656 2020-12-14 London 39
## 657 2020-12-15 London 49
## 658 2020-12-16 London 37
## 659 2020-12-17 London 57
## 660 2020-12-18 London 43
## 661 2020-12-19 London 41
## 662 2020-12-20 London 54
## 663 2020-12-21 London 60
## 664 2020-12-22 London 59
## 665 2020-12-23 London 57
## 666 2020-12-24 London 65
## 667 2020-12-25 London 82
## 668 2020-12-26 London 82
## 669 2020-12-27 London 92
## 670 2020-12-28 London 89
## 671 2020-12-29 London 110
## 672 2020-12-30 London 100
## 673 2020-12-31 London 110
## 674 2021-01-01 London 114
## 675 2021-01-02 London 126
## 676 2021-01-03 London 107
## 677 2021-01-04 London 148
## 678 2021-01-05 London 145
## 679 2021-01-06 London 146
## 680 2021-01-07 London 157
## 681 2021-01-08 London 138
## 682 2021-01-09 London 146
## 683 2021-01-10 London 160
## 684 2021-01-11 London 159
## 685 2021-01-12 London 170
## 686 2021-01-13 London 165
## 687 2021-01-14 London 154
## 688 2021-01-15 London 144
## 689 2021-01-16 London 158
## 690 2021-01-17 London 168
## 691 2021-01-18 London 182
## 692 2021-01-19 London 180
## 693 2021-01-20 London 156
## 694 2021-01-21 London 178
## 695 2021-01-22 London 139
## 696 2021-01-23 London 140
## 697 2021-01-24 London 128
## 698 2021-01-25 London 125
## 699 2021-01-26 London 118
## 700 2021-01-27 London 111
## 701 2021-01-28 London 109
## 702 2021-01-29 London 94
## 703 2021-01-30 London 88
## 704 2021-01-31 London 89
## 705 2021-02-01 London 77
## 706 2021-02-02 London 99
## 707 2021-02-03 London 107
## 708 2021-02-04 London 63
## 709 2021-02-05 London 85
## 710 2021-02-06 London 61
## 711 2021-02-07 London 68
## 712 2021-02-08 London 66
## 713 2021-02-09 London 56
## 714 2021-02-10 London 69
## 715 2021-02-11 London 47
## 716 2021-02-12 London 51
## 717 2021-02-13 London 43
## 718 2021-02-14 London 42
## 719 2021-02-15 London 37
## 720 2021-02-16 London 48
## 721 2021-02-17 London 43
## 722 2021-02-18 London 41
## 723 2021-02-19 London 41
## 724 2021-02-20 London 28
## 725 2021-02-21 London 35
## 726 2021-02-22 London 31
## 727 2021-02-23 London 23
## 728 2021-02-24 London 25
## 729 2021-02-25 London 19
## 730 2021-02-26 London 19
## 731 2021-02-27 London 15
## 732 2021-02-28 London 9
## 733 2021-03-01 London 10
## 734 2021-03-02 London 4
## 735 2020-03-01 Midlands 0
## 736 2020-03-02 Midlands 0
## 737 2020-03-03 Midlands 1
## 738 2020-03-04 Midlands 0
## 739 2020-03-05 Midlands 0
## 740 2020-03-06 Midlands 0
## 741 2020-03-07 Midlands 0
## 742 2020-03-08 Midlands 2
## 743 2020-03-09 Midlands 1
## 744 2020-03-10 Midlands 0
## 745 2020-03-11 Midlands 2
## 746 2020-03-12 Midlands 6
## 747 2020-03-13 Midlands 5
## 748 2020-03-14 Midlands 4
## 749 2020-03-15 Midlands 5
## 750 2020-03-16 Midlands 11
## 751 2020-03-17 Midlands 8
## 752 2020-03-18 Midlands 13
## 753 2020-03-19 Midlands 8
## 754 2020-03-20 Midlands 28
## 755 2020-03-21 Midlands 13
## 756 2020-03-22 Midlands 31
## 757 2020-03-23 Midlands 33
## 758 2020-03-24 Midlands 41
## 759 2020-03-25 Midlands 48
## 760 2020-03-26 Midlands 64
## 761 2020-03-27 Midlands 72
## 762 2020-03-28 Midlands 89
## 763 2020-03-29 Midlands 92
## 764 2020-03-30 Midlands 90
## 765 2020-03-31 Midlands 123
## 766 2020-04-01 Midlands 140
## 767 2020-04-02 Midlands 142
## 768 2020-04-03 Midlands 124
## 769 2020-04-04 Midlands 151
## 770 2020-04-05 Midlands 164
## 771 2020-04-06 Midlands 140
## 772 2020-04-07 Midlands 123
## 773 2020-04-08 Midlands 186
## 774 2020-04-09 Midlands 140
## 775 2020-04-10 Midlands 127
## 776 2020-04-11 Midlands 142
## 777 2020-04-12 Midlands 139
## 778 2020-04-13 Midlands 120
## 779 2020-04-14 Midlands 116
## 780 2020-04-15 Midlands 147
## 781 2020-04-16 Midlands 102
## 782 2020-04-17 Midlands 118
## 783 2020-04-18 Midlands 115
## 784 2020-04-19 Midlands 93
## 785 2020-04-20 Midlands 107
## 786 2020-04-21 Midlands 87
## 787 2020-04-22 Midlands 78
## 788 2020-04-23 Midlands 103
## 789 2020-04-24 Midlands 79
## 790 2020-04-25 Midlands 72
## 791 2020-04-26 Midlands 81
## 792 2020-04-27 Midlands 74
## 793 2020-04-28 Midlands 68
## 794 2020-04-29 Midlands 53
## 795 2020-04-30 Midlands 56
## 796 2020-05-01 Midlands 65
## 797 2020-05-02 Midlands 51
## 798 2020-05-03 Midlands 52
## 799 2020-05-04 Midlands 61
## 800 2020-05-05 Midlands 59
## 801 2020-05-06 Midlands 59
## 802 2020-05-07 Midlands 48
## 803 2020-05-08 Midlands 34
## 804 2020-05-09 Midlands 37
## 805 2020-05-10 Midlands 42
## 806 2020-05-11 Midlands 33
## 807 2020-05-12 Midlands 45
## 808 2020-05-13 Midlands 40
## 809 2020-05-14 Midlands 39
## 810 2020-05-15 Midlands 40
## 811 2020-05-16 Midlands 34
## 812 2020-05-17 Midlands 31
## 813 2020-05-18 Midlands 36
## 814 2020-05-19 Midlands 35
## 815 2020-05-20 Midlands 36
## 816 2020-05-21 Midlands 32
## 817 2020-05-22 Midlands 27
## 818 2020-05-23 Midlands 34
## 819 2020-05-24 Midlands 20
## 820 2020-05-25 Midlands 26
## 821 2020-05-26 Midlands 33
## 822 2020-05-27 Midlands 29
## 823 2020-05-28 Midlands 28
## 824 2020-05-29 Midlands 20
## 825 2020-05-30 Midlands 21
## 826 2020-05-31 Midlands 22
## 827 2020-06-01 Midlands 20
## 828 2020-06-02 Midlands 22
## 829 2020-06-03 Midlands 24
## 830 2020-06-04 Midlands 16
## 831 2020-06-05 Midlands 21
## 832 2020-06-06 Midlands 20
## 833 2020-06-07 Midlands 17
## 834 2020-06-08 Midlands 16
## 835 2020-06-09 Midlands 18
## 836 2020-06-10 Midlands 15
## 837 2020-06-11 Midlands 13
## 838 2020-06-12 Midlands 12
## 839 2020-06-13 Midlands 6
## 840 2020-06-14 Midlands 18
## 841 2020-06-15 Midlands 12
## 842 2020-06-16 Midlands 15
## 843 2020-06-17 Midlands 11
## 844 2020-06-18 Midlands 15
## 845 2020-06-19 Midlands 10
## 846 2020-06-20 Midlands 15
## 847 2020-06-21 Midlands 14
## 848 2020-06-22 Midlands 14
## 849 2020-06-23 Midlands 16
## 850 2020-06-24 Midlands 15
## 851 2020-06-25 Midlands 19
## 852 2020-06-26 Midlands 5
## 853 2020-06-27 Midlands 5
## 854 2020-06-28 Midlands 7
## 855 2020-06-29 Midlands 6
## 856 2020-06-30 Midlands 6
## 857 2020-07-01 Midlands 7
## 858 2020-07-02 Midlands 10
## 859 2020-07-03 Midlands 3
## 860 2020-07-04 Midlands 4
## 861 2020-07-05 Midlands 6
## 862 2020-07-06 Midlands 5
## 863 2020-07-07 Midlands 3
## 864 2020-07-08 Midlands 5
## 865 2020-07-09 Midlands 9
## 866 2020-07-10 Midlands 3
## 867 2020-07-11 Midlands 0
## 868 2020-07-12 Midlands 5
## 869 2020-07-13 Midlands 1
## 870 2020-07-14 Midlands 1
## 871 2020-07-15 Midlands 6
## 872 2020-07-16 Midlands 2
## 873 2020-07-17 Midlands 3
## 874 2020-07-18 Midlands 3
## 875 2020-07-19 Midlands 3
## 876 2020-07-20 Midlands 3
## 877 2020-07-21 Midlands 1
## 878 2020-07-22 Midlands 2
## 879 2020-07-23 Midlands 6
## 880 2020-07-24 Midlands 1
## 881 2020-07-25 Midlands 4
## 882 2020-07-26 Midlands 4
## 883 2020-07-27 Midlands 5
## 884 2020-07-28 Midlands 1
## 885 2020-07-29 Midlands 1
## 886 2020-07-30 Midlands 1
## 887 2020-07-31 Midlands 2
## 888 2020-08-01 Midlands 0
## 889 2020-08-02 Midlands 1
## 890 2020-08-03 Midlands 2
## 891 2020-08-04 Midlands 1
## 892 2020-08-05 Midlands 1
## 893 2020-08-06 Midlands 0
## 894 2020-08-07 Midlands 3
## 895 2020-08-08 Midlands 2
## 896 2020-08-09 Midlands 0
## 897 2020-08-10 Midlands 0
## 898 2020-08-11 Midlands 2
## 899 2020-08-12 Midlands 0
## 900 2020-08-13 Midlands 0
## 901 2020-08-14 Midlands 0
## 902 2020-08-15 Midlands 1
## 903 2020-08-16 Midlands 0
## 904 2020-08-17 Midlands 0
## 905 2020-08-18 Midlands 0
## 906 2020-08-19 Midlands 0
## 907 2020-08-20 Midlands 0
## 908 2020-08-21 Midlands 1
## 909 2020-08-22 Midlands 0
## 910 2020-08-23 Midlands 0
## 911 2020-08-24 Midlands 0
## 912 2020-08-25 Midlands 2
## 913 2020-08-26 Midlands 3
## 914 2020-08-27 Midlands 2
## 915 2020-08-28 Midlands 1
## 916 2020-08-29 Midlands 0
## 917 2020-08-30 Midlands 2
## 918 2020-08-31 Midlands 1
## 919 2020-09-01 Midlands 0
## 920 2020-09-02 Midlands 2
## 921 2020-09-03 Midlands 0
## 922 2020-09-04 Midlands 0
## 923 2020-09-05 Midlands 0
## 924 2020-09-06 Midlands 1
## 925 2020-09-07 Midlands 1
## 926 2020-09-08 Midlands 3
## 927 2020-09-09 Midlands 0
## 928 2020-09-10 Midlands 1
## 929 2020-09-11 Midlands 1
## 930 2020-09-12 Midlands 2
## 931 2020-09-13 Midlands 4
## 932 2020-09-14 Midlands 1
## 933 2020-09-15 Midlands 2
## 934 2020-09-16 Midlands 3
## 935 2020-09-17 Midlands 2
## 936 2020-09-18 Midlands 5
## 937 2020-09-19 Midlands 2
## 938 2020-09-20 Midlands 7
## 939 2020-09-21 Midlands 3
## 940 2020-09-22 Midlands 4
## 941 2020-09-23 Midlands 10
## 942 2020-09-24 Midlands 7
## 943 2020-09-25 Midlands 4
## 944 2020-09-26 Midlands 5
## 945 2020-09-27 Midlands 9
## 946 2020-09-28 Midlands 6
## 947 2020-09-29 Midlands 4
## 948 2020-09-30 Midlands 5
## 949 2020-10-01 Midlands 8
## 950 2020-10-02 Midlands 7
## 951 2020-10-03 Midlands 6
## 952 2020-10-04 Midlands 7
## 953 2020-10-05 Midlands 6
## 954 2020-10-06 Midlands 5
## 955 2020-10-07 Midlands 9
## 956 2020-10-08 Midlands 8
## 957 2020-10-09 Midlands 7
## 958 2020-10-10 Midlands 2
## 959 2020-10-11 Midlands 15
## 960 2020-10-12 Midlands 7
## 961 2020-10-13 Midlands 16
## 962 2020-10-14 Midlands 12
## 963 2020-10-15 Midlands 11
## 964 2020-10-16 Midlands 18
## 965 2020-10-17 Midlands 25
## 966 2020-10-18 Midlands 11
## 967 2020-10-19 Midlands 14
## 968 2020-10-20 Midlands 19
## 969 2020-10-21 Midlands 15
## 970 2020-10-22 Midlands 34
## 971 2020-10-23 Midlands 32
## 972 2020-10-24 Midlands 24
## 973 2020-10-25 Midlands 30
## 974 2020-10-26 Midlands 33
## 975 2020-10-27 Midlands 38
## 976 2020-10-28 Midlands 30
## 977 2020-10-29 Midlands 42
## 978 2020-10-30 Midlands 42
## 979 2020-10-31 Midlands 50
## 980 2020-11-01 Midlands 44
## 981 2020-11-02 Midlands 58
## 982 2020-11-03 Midlands 37
## 983 2020-11-04 Midlands 67
## 984 2020-11-05 Midlands 50
## 985 2020-11-06 Midlands 43
## 986 2020-11-07 Midlands 60
## 987 2020-11-08 Midlands 55
## 988 2020-11-09 Midlands 67
## 989 2020-11-10 Midlands 68
## 990 2020-11-11 Midlands 58
## 991 2020-11-12 Midlands 64
## 992 2020-11-13 Midlands 47
## 993 2020-11-14 Midlands 66
## 994 2020-11-15 Midlands 72
## 995 2020-11-16 Midlands 66
## 996 2020-11-17 Midlands 66
## 997 2020-11-18 Midlands 83
## 998 2020-11-19 Midlands 72
## 999 2020-11-20 Midlands 87
## 1000 2020-11-21 Midlands 59
## 1001 2020-11-22 Midlands 84
## 1002 2020-11-23 Midlands 80
## 1003 2020-11-24 Midlands 73
## 1004 2020-11-25 Midlands 74
## 1005 2020-11-26 Midlands 77
## 1006 2020-11-27 Midlands 78
## 1007 2020-11-28 Midlands 80
## 1008 2020-11-29 Midlands 86
## 1009 2020-11-30 Midlands 79
## 1010 2020-12-01 Midlands 74
## 1011 2020-12-02 Midlands 64
## 1012 2020-12-03 Midlands 82
## 1013 2020-12-04 Midlands 67
## 1014 2020-12-05 Midlands 71
## 1015 2020-12-06 Midlands 75
## 1016 2020-12-07 Midlands 68
## 1017 2020-12-08 Midlands 66
## 1018 2020-12-09 Midlands 63
## 1019 2020-12-10 Midlands 75
## 1020 2020-12-11 Midlands 65
## 1021 2020-12-12 Midlands 81
## 1022 2020-12-13 Midlands 78
## 1023 2020-12-14 Midlands 77
## 1024 2020-12-15 Midlands 73
## 1025 2020-12-16 Midlands 74
## 1026 2020-12-17 Midlands 86
## 1027 2020-12-18 Midlands 81
## 1028 2020-12-19 Midlands 57
## 1029 2020-12-20 Midlands 66
## 1030 2020-12-21 Midlands 85
## 1031 2020-12-22 Midlands 74
## 1032 2020-12-23 Midlands 58
## 1033 2020-12-24 Midlands 68
## 1034 2020-12-25 Midlands 81
## 1035 2020-12-26 Midlands 74
## 1036 2020-12-27 Midlands 87
## 1037 2020-12-28 Midlands 64
## 1038 2020-12-29 Midlands 83
## 1039 2020-12-30 Midlands 100
## 1040 2020-12-31 Midlands 89
## 1041 2021-01-01 Midlands 77
## 1042 2021-01-02 Midlands 76
## 1043 2021-01-03 Midlands 71
## 1044 2021-01-04 Midlands 95
## 1045 2021-01-05 Midlands 106
## 1046 2021-01-06 Midlands 112
## 1047 2021-01-07 Midlands 105
## 1048 2021-01-08 Midlands 131
## 1049 2021-01-09 Midlands 140
## 1050 2021-01-10 Midlands 122
## 1051 2021-01-11 Midlands 145
## 1052 2021-01-12 Midlands 161
## 1053 2021-01-13 Midlands 141
## 1054 2021-01-14 Midlands 157
## 1055 2021-01-15 Midlands 130
## 1056 2021-01-16 Midlands 150
## 1057 2021-01-17 Midlands 156
## 1058 2021-01-18 Midlands 160
## 1059 2021-01-19 Midlands 157
## 1060 2021-01-20 Midlands 146
## 1061 2021-01-21 Midlands 158
## 1062 2021-01-22 Midlands 159
## 1063 2021-01-23 Midlands 141
## 1064 2021-01-24 Midlands 165
## 1065 2021-01-25 Midlands 154
## 1066 2021-01-26 Midlands 143
## 1067 2021-01-27 Midlands 136
## 1068 2021-01-28 Midlands 136
## 1069 2021-01-29 Midlands 148
## 1070 2021-01-30 Midlands 124
## 1071 2021-01-31 Midlands 109
## 1072 2021-02-01 Midlands 136
## 1073 2021-02-02 Midlands 131
## 1074 2021-02-03 Midlands 132
## 1075 2021-02-04 Midlands 109
## 1076 2021-02-05 Midlands 110
## 1077 2021-02-06 Midlands 92
## 1078 2021-02-07 Midlands 108
## 1079 2021-02-08 Midlands 99
## 1080 2021-02-09 Midlands 96
## 1081 2021-02-10 Midlands 93
## 1082 2021-02-11 Midlands 89
## 1083 2021-02-12 Midlands 87
## 1084 2021-02-13 Midlands 66
## 1085 2021-02-14 Midlands 81
## 1086 2021-02-15 Midlands 84
## 1087 2021-02-16 Midlands 76
## 1088 2021-02-17 Midlands 65
## 1089 2021-02-18 Midlands 66
## 1090 2021-02-19 Midlands 54
## 1091 2021-02-20 Midlands 67
## 1092 2021-02-21 Midlands 56
## 1093 2021-02-22 Midlands 53
## 1094 2021-02-23 Midlands 55
## 1095 2021-02-24 Midlands 50
## 1096 2021-02-25 Midlands 52
## 1097 2021-02-26 Midlands 40
## 1098 2021-02-27 Midlands 40
## 1099 2021-02-28 Midlands 42
## 1100 2021-03-01 Midlands 30
## 1101 2021-03-02 Midlands 4
## 1102 2020-03-01 North East and Yorkshire 0
## 1103 2020-03-02 North East and Yorkshire 0
## 1104 2020-03-03 North East and Yorkshire 0
## 1105 2020-03-04 North East and Yorkshire 0
## 1106 2020-03-05 North East and Yorkshire 0
## 1107 2020-03-06 North East and Yorkshire 0
## 1108 2020-03-07 North East and Yorkshire 0
## 1109 2020-03-08 North East and Yorkshire 0
## 1110 2020-03-09 North East and Yorkshire 0
## 1111 2020-03-10 North East and Yorkshire 0
## 1112 2020-03-11 North East and Yorkshire 0
## 1113 2020-03-12 North East and Yorkshire 0
## 1114 2020-03-13 North East and Yorkshire 0
## 1115 2020-03-14 North East and Yorkshire 0
## 1116 2020-03-15 North East and Yorkshire 2
## 1117 2020-03-16 North East and Yorkshire 3
## 1118 2020-03-17 North East and Yorkshire 1
## 1119 2020-03-18 North East and Yorkshire 2
## 1120 2020-03-19 North East and Yorkshire 6
## 1121 2020-03-20 North East and Yorkshire 5
## 1122 2020-03-21 North East and Yorkshire 6
## 1123 2020-03-22 North East and Yorkshire 7
## 1124 2020-03-23 North East and Yorkshire 9
## 1125 2020-03-24 North East and Yorkshire 8
## 1126 2020-03-25 North East and Yorkshire 18
## 1127 2020-03-26 North East and Yorkshire 21
## 1128 2020-03-27 North East and Yorkshire 28
## 1129 2020-03-28 North East and Yorkshire 35
## 1130 2020-03-29 North East and Yorkshire 38
## 1131 2020-03-30 North East and Yorkshire 64
## 1132 2020-03-31 North East and Yorkshire 60
## 1133 2020-04-01 North East and Yorkshire 67
## 1134 2020-04-02 North East and Yorkshire 75
## 1135 2020-04-03 North East and Yorkshire 100
## 1136 2020-04-04 North East and Yorkshire 105
## 1137 2020-04-05 North East and Yorkshire 92
## 1138 2020-04-06 North East and Yorkshire 96
## 1139 2020-04-07 North East and Yorkshire 102
## 1140 2020-04-08 North East and Yorkshire 107
## 1141 2020-04-09 North East and Yorkshire 111
## 1142 2020-04-10 North East and Yorkshire 117
## 1143 2020-04-11 North East and Yorkshire 98
## 1144 2020-04-12 North East and Yorkshire 84
## 1145 2020-04-13 North East and Yorkshire 94
## 1146 2020-04-14 North East and Yorkshire 107
## 1147 2020-04-15 North East and Yorkshire 96
## 1148 2020-04-16 North East and Yorkshire 103
## 1149 2020-04-17 North East and Yorkshire 88
## 1150 2020-04-18 North East and Yorkshire 95
## 1151 2020-04-19 North East and Yorkshire 88
## 1152 2020-04-20 North East and Yorkshire 100
## 1153 2020-04-21 North East and Yorkshire 76
## 1154 2020-04-22 North East and Yorkshire 84
## 1155 2020-04-23 North East and Yorkshire 63
## 1156 2020-04-24 North East and Yorkshire 72
## 1157 2020-04-25 North East and Yorkshire 69
## 1158 2020-04-26 North East and Yorkshire 65
## 1159 2020-04-27 North East and Yorkshire 65
## 1160 2020-04-28 North East and Yorkshire 57
## 1161 2020-04-29 North East and Yorkshire 69
## 1162 2020-04-30 North East and Yorkshire 57
## 1163 2020-05-01 North East and Yorkshire 64
## 1164 2020-05-02 North East and Yorkshire 48
## 1165 2020-05-03 North East and Yorkshire 40
## 1166 2020-05-04 North East and Yorkshire 49
## 1167 2020-05-05 North East and Yorkshire 40
## 1168 2020-05-06 North East and Yorkshire 51
## 1169 2020-05-07 North East and Yorkshire 45
## 1170 2020-05-08 North East and Yorkshire 42
## 1171 2020-05-09 North East and Yorkshire 44
## 1172 2020-05-10 North East and Yorkshire 40
## 1173 2020-05-11 North East and Yorkshire 29
## 1174 2020-05-12 North East and Yorkshire 27
## 1175 2020-05-13 North East and Yorkshire 28
## 1176 2020-05-14 North East and Yorkshire 31
## 1177 2020-05-15 North East and Yorkshire 32
## 1178 2020-05-16 North East and Yorkshire 35
## 1179 2020-05-17 North East and Yorkshire 26
## 1180 2020-05-18 North East and Yorkshire 30
## 1181 2020-05-19 North East and Yorkshire 27
## 1182 2020-05-20 North East and Yorkshire 22
## 1183 2020-05-21 North East and Yorkshire 33
## 1184 2020-05-22 North East and Yorkshire 22
## 1185 2020-05-23 North East and Yorkshire 18
## 1186 2020-05-24 North East and Yorkshire 26
## 1187 2020-05-25 North East and Yorkshire 21
## 1188 2020-05-26 North East and Yorkshire 21
## 1189 2020-05-27 North East and Yorkshire 23
## 1190 2020-05-28 North East and Yorkshire 21
## 1191 2020-05-29 North East and Yorkshire 25
## 1192 2020-05-30 North East and Yorkshire 20
## 1193 2020-05-31 North East and Yorkshire 20
## 1194 2020-06-01 North East and Yorkshire 17
## 1195 2020-06-02 North East and Yorkshire 23
## 1196 2020-06-03 North East and Yorkshire 24
## 1197 2020-06-04 North East and Yorkshire 17
## 1198 2020-06-05 North East and Yorkshire 18
## 1199 2020-06-06 North East and Yorkshire 21
## 1200 2020-06-07 North East and Yorkshire 14
## 1201 2020-06-08 North East and Yorkshire 11
## 1202 2020-06-09 North East and Yorkshire 12
## 1203 2020-06-10 North East and Yorkshire 19
## 1204 2020-06-11 North East and Yorkshire 7
## 1205 2020-06-12 North East and Yorkshire 9
## 1206 2020-06-13 North East and Yorkshire 10
## 1207 2020-06-14 North East and Yorkshire 11
## 1208 2020-06-15 North East and Yorkshire 9
## 1209 2020-06-16 North East and Yorkshire 10
## 1210 2020-06-17 North East and Yorkshire 9
## 1211 2020-06-18 North East and Yorkshire 11
## 1212 2020-06-19 North East and Yorkshire 6
## 1213 2020-06-20 North East and Yorkshire 5
## 1214 2020-06-21 North East and Yorkshire 4
## 1215 2020-06-22 North East and Yorkshire 7
## 1216 2020-06-23 North East and Yorkshire 8
## 1217 2020-06-24 North East and Yorkshire 10
## 1218 2020-06-25 North East and Yorkshire 4
## 1219 2020-06-26 North East and Yorkshire 8
## 1220 2020-06-27 North East and Yorkshire 4
## 1221 2020-06-28 North East and Yorkshire 5
## 1222 2020-06-29 North East and Yorkshire 2
## 1223 2020-06-30 North East and Yorkshire 7
## 1224 2020-07-01 North East and Yorkshire 1
## 1225 2020-07-02 North East and Yorkshire 5
## 1226 2020-07-03 North East and Yorkshire 4
## 1227 2020-07-04 North East and Yorkshire 4
## 1228 2020-07-05 North East and Yorkshire 3
## 1229 2020-07-06 North East and Yorkshire 2
## 1230 2020-07-07 North East and Yorkshire 3
## 1231 2020-07-08 North East and Yorkshire 3
## 1232 2020-07-09 North East and Yorkshire 0
## 1233 2020-07-10 North East and Yorkshire 3
## 1234 2020-07-11 North East and Yorkshire 1
## 1235 2020-07-12 North East and Yorkshire 4
## 1236 2020-07-13 North East and Yorkshire 1
## 1237 2020-07-14 North East and Yorkshire 1
## 1238 2020-07-15 North East and Yorkshire 2
## 1239 2020-07-16 North East and Yorkshire 3
## 1240 2020-07-17 North East and Yorkshire 1
## 1241 2020-07-18 North East and Yorkshire 2
## 1242 2020-07-19 North East and Yorkshire 2
## 1243 2020-07-20 North East and Yorkshire 1
## 1244 2020-07-21 North East and Yorkshire 1
## 1245 2020-07-22 North East and Yorkshire 6
## 1246 2020-07-23 North East and Yorkshire 0
## 1247 2020-07-24 North East and Yorkshire 1
## 1248 2020-07-25 North East and Yorkshire 5
## 1249 2020-07-26 North East and Yorkshire 1
## 1250 2020-07-27 North East and Yorkshire 0
## 1251 2020-07-28 North East and Yorkshire 2
## 1252 2020-07-29 North East and Yorkshire 1
## 1253 2020-07-30 North East and Yorkshire 0
## 1254 2020-07-31 North East and Yorkshire 1
## 1255 2020-08-01 North East and Yorkshire 3
## 1256 2020-08-02 North East and Yorkshire 2
## 1257 2020-08-03 North East and Yorkshire 1
## 1258 2020-08-04 North East and Yorkshire 3
## 1259 2020-08-05 North East and Yorkshire 1
## 1260 2020-08-06 North East and Yorkshire 4
## 1261 2020-08-07 North East and Yorkshire 0
## 1262 2020-08-08 North East and Yorkshire 2
## 1263 2020-08-09 North East and Yorkshire 3
## 1264 2020-08-10 North East and Yorkshire 3
## 1265 2020-08-11 North East and Yorkshire 2
## 1266 2020-08-12 North East and Yorkshire 2
## 1267 2020-08-13 North East and Yorkshire 0
## 1268 2020-08-14 North East and Yorkshire 1
## 1269 2020-08-15 North East and Yorkshire 1
## 1270 2020-08-16 North East and Yorkshire 0
## 1271 2020-08-17 North East and Yorkshire 6
## 1272 2020-08-18 North East and Yorkshire 1
## 1273 2020-08-19 North East and Yorkshire 0
## 1274 2020-08-20 North East and Yorkshire 0
## 1275 2020-08-21 North East and Yorkshire 1
## 1276 2020-08-22 North East and Yorkshire 1
## 1277 2020-08-23 North East and Yorkshire 3
## 1278 2020-08-24 North East and Yorkshire 0
## 1279 2020-08-25 North East and Yorkshire 2
## 1280 2020-08-26 North East and Yorkshire 2
## 1281 2020-08-27 North East and Yorkshire 1
## 1282 2020-08-28 North East and Yorkshire 0
## 1283 2020-08-29 North East and Yorkshire 1
## 1284 2020-08-30 North East and Yorkshire 0
## 1285 2020-08-31 North East and Yorkshire 0
## 1286 2020-09-01 North East and Yorkshire 2
## 1287 2020-09-02 North East and Yorkshire 3
## 1288 2020-09-03 North East and Yorkshire 1
## 1289 2020-09-04 North East and Yorkshire 1
## 1290 2020-09-05 North East and Yorkshire 2
## 1291 2020-09-06 North East and Yorkshire 1
## 1292 2020-09-07 North East and Yorkshire 0
## 1293 2020-09-08 North East and Yorkshire 1
## 1294 2020-09-09 North East and Yorkshire 2
## 1295 2020-09-10 North East and Yorkshire 0
## 1296 2020-09-11 North East and Yorkshire 3
## 1297 2020-09-12 North East and Yorkshire 1
## 1298 2020-09-13 North East and Yorkshire 3
## 1299 2020-09-14 North East and Yorkshire 4
## 1300 2020-09-15 North East and Yorkshire 3
## 1301 2020-09-16 North East and Yorkshire 3
## 1302 2020-09-17 North East and Yorkshire 5
## 1303 2020-09-18 North East and Yorkshire 6
## 1304 2020-09-19 North East and Yorkshire 2
## 1305 2020-09-20 North East and Yorkshire 9
## 1306 2020-09-21 North East and Yorkshire 7
## 1307 2020-09-22 North East and Yorkshire 5
## 1308 2020-09-23 North East and Yorkshire 6
## 1309 2020-09-24 North East and Yorkshire 3
## 1310 2020-09-25 North East and Yorkshire 5
## 1311 2020-09-26 North East and Yorkshire 7
## 1312 2020-09-27 North East and Yorkshire 10
## 1313 2020-09-28 North East and Yorkshire 6
## 1314 2020-09-29 North East and Yorkshire 7
## 1315 2020-09-30 North East and Yorkshire 7
## 1316 2020-10-01 North East and Yorkshire 8
## 1317 2020-10-02 North East and Yorkshire 16
## 1318 2020-10-03 North East and Yorkshire 12
## 1319 2020-10-04 North East and Yorkshire 13
## 1320 2020-10-05 North East and Yorkshire 10
## 1321 2020-10-06 North East and Yorkshire 15
## 1322 2020-10-07 North East and Yorkshire 13
## 1323 2020-10-08 North East and Yorkshire 16
## 1324 2020-10-09 North East and Yorkshire 10
## 1325 2020-10-10 North East and Yorkshire 16
## 1326 2020-10-11 North East and Yorkshire 16
## 1327 2020-10-12 North East and Yorkshire 15
## 1328 2020-10-13 North East and Yorkshire 21
## 1329 2020-10-14 North East and Yorkshire 20
## 1330 2020-10-15 North East and Yorkshire 23
## 1331 2020-10-16 North East and Yorkshire 24
## 1332 2020-10-17 North East and Yorkshire 34
## 1333 2020-10-18 North East and Yorkshire 22
## 1334 2020-10-19 North East and Yorkshire 34
## 1335 2020-10-20 North East and Yorkshire 37
## 1336 2020-10-21 North East and Yorkshire 43
## 1337 2020-10-22 North East and Yorkshire 33
## 1338 2020-10-23 North East and Yorkshire 31
## 1339 2020-10-24 North East and Yorkshire 34
## 1340 2020-10-25 North East and Yorkshire 35
## 1341 2020-10-26 North East and Yorkshire 46
## 1342 2020-10-27 North East and Yorkshire 45
## 1343 2020-10-28 North East and Yorkshire 39
## 1344 2020-10-29 North East and Yorkshire 51
## 1345 2020-10-30 North East and Yorkshire 48
## 1346 2020-10-31 North East and Yorkshire 58
## 1347 2020-11-01 North East and Yorkshire 48
## 1348 2020-11-02 North East and Yorkshire 50
## 1349 2020-11-03 North East and Yorkshire 48
## 1350 2020-11-04 North East and Yorkshire 57
## 1351 2020-11-05 North East and Yorkshire 57
## 1352 2020-11-06 North East and Yorkshire 57
## 1353 2020-11-07 North East and Yorkshire 75
## 1354 2020-11-08 North East and Yorkshire 62
## 1355 2020-11-09 North East and Yorkshire 87
## 1356 2020-11-10 North East and Yorkshire 65
## 1357 2020-11-11 North East and Yorkshire 59
## 1358 2020-11-12 North East and Yorkshire 77
## 1359 2020-11-13 North East and Yorkshire 78
## 1360 2020-11-14 North East and Yorkshire 72
## 1361 2020-11-15 North East and Yorkshire 77
## 1362 2020-11-16 North East and Yorkshire 52
## 1363 2020-11-17 North East and Yorkshire 68
## 1364 2020-11-18 North East and Yorkshire 81
## 1365 2020-11-19 North East and Yorkshire 72
## 1366 2020-11-20 North East and Yorkshire 75
## 1367 2020-11-21 North East and Yorkshire 54
## 1368 2020-11-22 North East and Yorkshire 80
## 1369 2020-11-23 North East and Yorkshire 84
## 1370 2020-11-24 North East and Yorkshire 81
## 1371 2020-11-25 North East and Yorkshire 70
## 1372 2020-11-26 North East and Yorkshire 64
## 1373 2020-11-27 North East and Yorkshire 62
## 1374 2020-11-28 North East and Yorkshire 77
## 1375 2020-11-29 North East and Yorkshire 61
## 1376 2020-11-30 North East and Yorkshire 56
## 1377 2020-12-01 North East and Yorkshire 44
## 1378 2020-12-02 North East and Yorkshire 59
## 1379 2020-12-03 North East and Yorkshire 71
## 1380 2020-12-04 North East and Yorkshire 65
## 1381 2020-12-05 North East and Yorkshire 48
## 1382 2020-12-06 North East and Yorkshire 65
## 1383 2020-12-07 North East and Yorkshire 49
## 1384 2020-12-08 North East and Yorkshire 54
## 1385 2020-12-09 North East and Yorkshire 49
## 1386 2020-12-10 North East and Yorkshire 56
## 1387 2020-12-11 North East and Yorkshire 56
## 1388 2020-12-12 North East and Yorkshire 55
## 1389 2020-12-13 North East and Yorkshire 51
## 1390 2020-12-14 North East and Yorkshire 49
## 1391 2020-12-15 North East and Yorkshire 55
## 1392 2020-12-16 North East and Yorkshire 40
## 1393 2020-12-17 North East and Yorkshire 49
## 1394 2020-12-18 North East and Yorkshire 58
## 1395 2020-12-19 North East and Yorkshire 49
## 1396 2020-12-20 North East and Yorkshire 52
## 1397 2020-12-21 North East and Yorkshire 35
## 1398 2020-12-22 North East and Yorkshire 57
## 1399 2020-12-23 North East and Yorkshire 60
## 1400 2020-12-24 North East and Yorkshire 50
## 1401 2020-12-25 North East and Yorkshire 57
## 1402 2020-12-26 North East and Yorkshire 67
## 1403 2020-12-27 North East and Yorkshire 73
## 1404 2020-12-28 North East and Yorkshire 64
## 1405 2020-12-29 North East and Yorkshire 58
## 1406 2020-12-30 North East and Yorkshire 41
## 1407 2020-12-31 North East and Yorkshire 51
## 1408 2021-01-01 North East and Yorkshire 70
## 1409 2021-01-02 North East and Yorkshire 58
## 1410 2021-01-03 North East and Yorkshire 48
## 1411 2021-01-04 North East and Yorkshire 63
## 1412 2021-01-05 North East and Yorkshire 64
## 1413 2021-01-06 North East and Yorkshire 61
## 1414 2021-01-07 North East and Yorkshire 72
## 1415 2021-01-08 North East and Yorkshire 67
## 1416 2021-01-09 North East and Yorkshire 58
## 1417 2021-01-10 North East and Yorkshire 80
## 1418 2021-01-11 North East and Yorkshire 82
## 1419 2021-01-12 North East and Yorkshire 68
## 1420 2021-01-13 North East and Yorkshire 76
## 1421 2021-01-14 North East and Yorkshire 69
## 1422 2021-01-15 North East and Yorkshire 97
## 1423 2021-01-16 North East and Yorkshire 99
## 1424 2021-01-17 North East and Yorkshire 75
## 1425 2021-01-18 North East and Yorkshire 82
## 1426 2021-01-19 North East and Yorkshire 104
## 1427 2021-01-20 North East and Yorkshire 92
## 1428 2021-01-21 North East and Yorkshire 87
## 1429 2021-01-22 North East and Yorkshire 78
## 1430 2021-01-23 North East and Yorkshire 68
## 1431 2021-01-24 North East and Yorkshire 62
## 1432 2021-01-25 North East and Yorkshire 79
## 1433 2021-01-26 North East and Yorkshire 73
## 1434 2021-01-27 North East and Yorkshire 69
## 1435 2021-01-28 North East and Yorkshire 72
## 1436 2021-01-29 North East and Yorkshire 83
## 1437 2021-01-30 North East and Yorkshire 76
## 1438 2021-01-31 North East and Yorkshire 81
## 1439 2021-02-01 North East and Yorkshire 79
## 1440 2021-02-02 North East and Yorkshire 68
## 1441 2021-02-03 North East and Yorkshire 81
## 1442 2021-02-04 North East and Yorkshire 67
## 1443 2021-02-05 North East and Yorkshire 77
## 1444 2021-02-06 North East and Yorkshire 52
## 1445 2021-02-07 North East and Yorkshire 56
## 1446 2021-02-08 North East and Yorkshire 51
## 1447 2021-02-09 North East and Yorkshire 51
## 1448 2021-02-10 North East and Yorkshire 62
## 1449 2021-02-11 North East and Yorkshire 62
## 1450 2021-02-12 North East and Yorkshire 57
## 1451 2021-02-13 North East and Yorkshire 52
## 1452 2021-02-14 North East and Yorkshire 58
## 1453 2021-02-15 North East and Yorkshire 58
## 1454 2021-02-16 North East and Yorkshire 42
## 1455 2021-02-17 North East and Yorkshire 47
## 1456 2021-02-18 North East and Yorkshire 41
## 1457 2021-02-19 North East and Yorkshire 42
## 1458 2021-02-20 North East and Yorkshire 36
## 1459 2021-02-21 North East and Yorkshire 38
## 1460 2021-02-22 North East and Yorkshire 20
## 1461 2021-02-23 North East and Yorkshire 36
## 1462 2021-02-24 North East and Yorkshire 31
## 1463 2021-02-25 North East and Yorkshire 26
## 1464 2021-02-26 North East and Yorkshire 23
## 1465 2021-02-27 North East and Yorkshire 31
## 1466 2021-02-28 North East and Yorkshire 23
## 1467 2021-03-01 North East and Yorkshire 13
## 1468 2021-03-02 North East and Yorkshire 5
## 1469 2020-03-01 North West 0
## 1470 2020-03-02 North West 0
## 1471 2020-03-03 North West 0
## 1472 2020-03-04 North West 0
## 1473 2020-03-05 North West 1
## 1474 2020-03-06 North West 0
## 1475 2020-03-07 North West 0
## 1476 2020-03-08 North West 1
## 1477 2020-03-09 North West 0
## 1478 2020-03-10 North West 0
## 1479 2020-03-11 North West 0
## 1480 2020-03-12 North West 2
## 1481 2020-03-13 North West 3
## 1482 2020-03-14 North West 1
## 1483 2020-03-15 North West 4
## 1484 2020-03-16 North West 2
## 1485 2020-03-17 North West 4
## 1486 2020-03-18 North West 6
## 1487 2020-03-19 North West 7
## 1488 2020-03-20 North West 10
## 1489 2020-03-21 North West 11
## 1490 2020-03-22 North West 13
## 1491 2020-03-23 North West 15
## 1492 2020-03-24 North West 21
## 1493 2020-03-25 North West 21
## 1494 2020-03-26 North West 29
## 1495 2020-03-27 North West 36
## 1496 2020-03-28 North West 28
## 1497 2020-03-29 North West 46
## 1498 2020-03-30 North West 67
## 1499 2020-03-31 North West 52
## 1500 2020-04-01 North West 86
## 1501 2020-04-02 North West 96
## 1502 2020-04-03 North West 95
## 1503 2020-04-04 North West 98
## 1504 2020-04-05 North West 102
## 1505 2020-04-06 North West 100
## 1506 2020-04-07 North West 136
## 1507 2020-04-08 North West 127
## 1508 2020-04-09 North West 119
## 1509 2020-04-10 North West 117
## 1510 2020-04-11 North West 138
## 1511 2020-04-12 North West 125
## 1512 2020-04-13 North West 130
## 1513 2020-04-14 North West 130
## 1514 2020-04-15 North West 114
## 1515 2020-04-16 North West 135
## 1516 2020-04-17 North West 98
## 1517 2020-04-18 North West 114
## 1518 2020-04-19 North West 71
## 1519 2020-04-20 North West 83
## 1520 2020-04-21 North West 76
## 1521 2020-04-22 North West 87
## 1522 2020-04-23 North West 85
## 1523 2020-04-24 North West 67
## 1524 2020-04-25 North West 67
## 1525 2020-04-26 North West 55
## 1526 2020-04-27 North West 54
## 1527 2020-04-28 North West 57
## 1528 2020-04-29 North West 64
## 1529 2020-04-30 North West 60
## 1530 2020-05-01 North West 45
## 1531 2020-05-02 North West 56
## 1532 2020-05-03 North West 55
## 1533 2020-05-04 North West 48
## 1534 2020-05-05 North West 49
## 1535 2020-05-06 North West 44
## 1536 2020-05-07 North West 50
## 1537 2020-05-08 North West 43
## 1538 2020-05-09 North West 31
## 1539 2020-05-10 North West 42
## 1540 2020-05-11 North West 35
## 1541 2020-05-12 North West 38
## 1542 2020-05-13 North West 25
## 1543 2020-05-14 North West 26
## 1544 2020-05-15 North West 33
## 1545 2020-05-16 North West 32
## 1546 2020-05-17 North West 24
## 1547 2020-05-18 North West 31
## 1548 2020-05-19 North West 35
## 1549 2020-05-20 North West 27
## 1550 2020-05-21 North West 28
## 1551 2020-05-22 North West 26
## 1552 2020-05-23 North West 31
## 1553 2020-05-24 North West 26
## 1554 2020-05-25 North West 31
## 1555 2020-05-26 North West 27
## 1556 2020-05-27 North West 27
## 1557 2020-05-28 North West 28
## 1558 2020-05-29 North West 20
## 1559 2020-05-30 North West 19
## 1560 2020-05-31 North West 13
## 1561 2020-06-01 North West 12
## 1562 2020-06-02 North West 27
## 1563 2020-06-03 North West 22
## 1564 2020-06-04 North West 22
## 1565 2020-06-05 North West 16
## 1566 2020-06-06 North West 26
## 1567 2020-06-07 North West 20
## 1568 2020-06-08 North West 23
## 1569 2020-06-09 North West 17
## 1570 2020-06-10 North West 16
## 1571 2020-06-11 North West 16
## 1572 2020-06-12 North West 11
## 1573 2020-06-13 North West 10
## 1574 2020-06-14 North West 15
## 1575 2020-06-15 North West 16
## 1576 2020-06-16 North West 16
## 1577 2020-06-17 North West 13
## 1578 2020-06-18 North West 14
## 1579 2020-06-19 North West 7
## 1580 2020-06-20 North West 11
## 1581 2020-06-21 North West 8
## 1582 2020-06-22 North West 11
## 1583 2020-06-23 North West 13
## 1584 2020-06-24 North West 13
## 1585 2020-06-25 North West 15
## 1586 2020-06-26 North West 6
## 1587 2020-06-27 North West 7
## 1588 2020-06-28 North West 9
## 1589 2020-06-29 North West 9
## 1590 2020-06-30 North West 7
## 1591 2020-07-01 North West 3
## 1592 2020-07-02 North West 6
## 1593 2020-07-03 North West 7
## 1594 2020-07-04 North West 4
## 1595 2020-07-05 North West 6
## 1596 2020-07-06 North West 9
## 1597 2020-07-07 North West 8
## 1598 2020-07-08 North West 5
## 1599 2020-07-09 North West 10
## 1600 2020-07-10 North West 2
## 1601 2020-07-11 North West 5
## 1602 2020-07-12 North West 0
## 1603 2020-07-13 North West 6
## 1604 2020-07-14 North West 4
## 1605 2020-07-15 North West 5
## 1606 2020-07-16 North West 2
## 1607 2020-07-17 North West 4
## 1608 2020-07-18 North West 5
## 1609 2020-07-19 North West 3
## 1610 2020-07-20 North West 0
## 1611 2020-07-21 North West 2
## 1612 2020-07-22 North West 3
## 1613 2020-07-23 North West 3
## 1614 2020-07-24 North West 1
## 1615 2020-07-25 North West 1
## 1616 2020-07-26 North West 3
## 1617 2020-07-27 North West 1
## 1618 2020-07-28 North West 1
## 1619 2020-07-29 North West 2
## 1620 2020-07-30 North West 2
## 1621 2020-07-31 North West 0
## 1622 2020-08-01 North West 2
## 1623 2020-08-02 North West 1
## 1624 2020-08-03 North West 8
## 1625 2020-08-04 North West 3
## 1626 2020-08-05 North West 2
## 1627 2020-08-06 North West 2
## 1628 2020-08-07 North West 2
## 1629 2020-08-08 North West 2
## 1630 2020-08-09 North West 3
## 1631 2020-08-10 North West 2
## 1632 2020-08-11 North West 3
## 1633 2020-08-12 North West 0
## 1634 2020-08-13 North West 2
## 1635 2020-08-14 North West 2
## 1636 2020-08-15 North West 6
## 1637 2020-08-16 North West 2
## 1638 2020-08-17 North West 1
## 1639 2020-08-18 North West 2
## 1640 2020-08-19 North West 1
## 1641 2020-08-20 North West 1
## 1642 2020-08-21 North West 4
## 1643 2020-08-22 North West 3
## 1644 2020-08-23 North West 5
## 1645 2020-08-24 North West 4
## 1646 2020-08-25 North West 3
## 1647 2020-08-26 North West 4
## 1648 2020-08-27 North West 1
## 1649 2020-08-28 North West 2
## 1650 2020-08-29 North West 0
## 1651 2020-08-30 North West 2
## 1652 2020-08-31 North West 3
## 1653 2020-09-01 North West 0
## 1654 2020-09-02 North West 2
## 1655 2020-09-03 North West 1
## 1656 2020-09-04 North West 3
## 1657 2020-09-05 North West 6
## 1658 2020-09-06 North West 1
## 1659 2020-09-07 North West 8
## 1660 2020-09-08 North West 6
## 1661 2020-09-09 North West 5
## 1662 2020-09-10 North West 5
## 1663 2020-09-11 North West 1
## 1664 2020-09-12 North West 4
## 1665 2020-09-13 North West 2
## 1666 2020-09-14 North West 4
## 1667 2020-09-15 North West 4
## 1668 2020-09-16 North West 6
## 1669 2020-09-17 North West 7
## 1670 2020-09-18 North West 6
## 1671 2020-09-19 North West 3
## 1672 2020-09-20 North West 2
## 1673 2020-09-21 North West 2
## 1674 2020-09-22 North West 9
## 1675 2020-09-23 North West 14
## 1676 2020-09-24 North West 10
## 1677 2020-09-25 North West 8
## 1678 2020-09-26 North West 14
## 1679 2020-09-27 North West 11
## 1680 2020-09-28 North West 15
## 1681 2020-09-29 North West 12
## 1682 2020-09-30 North West 17
## 1683 2020-10-01 North West 17
## 1684 2020-10-02 North West 20
## 1685 2020-10-03 North West 15
## 1686 2020-10-04 North West 15
## 1687 2020-10-05 North West 15
## 1688 2020-10-06 North West 20
## 1689 2020-10-07 North West 20
## 1690 2020-10-08 North West 22
## 1691 2020-10-09 North West 24
## 1692 2020-10-10 North West 31
## 1693 2020-10-11 North West 31
## 1694 2020-10-12 North West 35
## 1695 2020-10-13 North West 26
## 1696 2020-10-14 North West 35
## 1697 2020-10-15 North West 36
## 1698 2020-10-16 North West 34
## 1699 2020-10-17 North West 52
## 1700 2020-10-18 North West 40
## 1701 2020-10-19 North West 43
## 1702 2020-10-20 North West 48
## 1703 2020-10-21 North West 51
## 1704 2020-10-22 North West 49
## 1705 2020-10-23 North West 50
## 1706 2020-10-24 North West 51
## 1707 2020-10-25 North West 63
## 1708 2020-10-26 North West 53
## 1709 2020-10-27 North West 49
## 1710 2020-10-28 North West 57
## 1711 2020-10-29 North West 74
## 1712 2020-10-30 North West 73
## 1713 2020-10-31 North West 63
## 1714 2020-11-01 North West 76
## 1715 2020-11-02 North West 65
## 1716 2020-11-03 North West 77
## 1717 2020-11-04 North West 64
## 1718 2020-11-05 North West 67
## 1719 2020-11-06 North West 76
## 1720 2020-11-07 North West 79
## 1721 2020-11-08 North West 83
## 1722 2020-11-09 North West 82
## 1723 2020-11-10 North West 68
## 1724 2020-11-11 North West 62
## 1725 2020-11-12 North West 64
## 1726 2020-11-13 North West 81
## 1727 2020-11-14 North West 61
## 1728 2020-11-15 North West 75
## 1729 2020-11-16 North West 74
## 1730 2020-11-17 North West 73
## 1731 2020-11-18 North West 71
## 1732 2020-11-19 North West 67
## 1733 2020-11-20 North West 52
## 1734 2020-11-21 North West 68
## 1735 2020-11-22 North West 52
## 1736 2020-11-23 North West 54
## 1737 2020-11-24 North West 64
## 1738 2020-11-25 North West 65
## 1739 2020-11-26 North West 53
## 1740 2020-11-27 North West 51
## 1741 2020-11-28 North West 46
## 1742 2020-11-29 North West 54
## 1743 2020-11-30 North West 48
## 1744 2020-12-01 North West 53
## 1745 2020-12-02 North West 48
## 1746 2020-12-03 North West 47
## 1747 2020-12-04 North West 48
## 1748 2020-12-05 North West 37
## 1749 2020-12-06 North West 43
## 1750 2020-12-07 North West 50
## 1751 2020-12-08 North West 49
## 1752 2020-12-09 North West 48
## 1753 2020-12-10 North West 49
## 1754 2020-12-11 North West 41
## 1755 2020-12-12 North West 48
## 1756 2020-12-13 North West 41
## 1757 2020-12-14 North West 51
## 1758 2020-12-15 North West 34
## 1759 2020-12-16 North West 41
## 1760 2020-12-17 North West 26
## 1761 2020-12-18 North West 47
## 1762 2020-12-19 North West 45
## 1763 2020-12-20 North West 37
## 1764 2020-12-21 North West 51
## 1765 2020-12-22 North West 52
## 1766 2020-12-23 North West 50
## 1767 2020-12-24 North West 58
## 1768 2020-12-25 North West 52
## 1769 2020-12-26 North West 56
## 1770 2020-12-27 North West 50
## 1771 2020-12-28 North West 48
## 1772 2020-12-29 North West 49
## 1773 2020-12-30 North West 49
## 1774 2020-12-31 North West 62
## 1775 2021-01-01 North West 54
## 1776 2021-01-02 North West 55
## 1777 2021-01-03 North West 57
## 1778 2021-01-04 North West 51
## 1779 2021-01-05 North West 56
## 1780 2021-01-06 North West 69
## 1781 2021-01-07 North West 61
## 1782 2021-01-08 North West 65
## 1783 2021-01-09 North West 69
## 1784 2021-01-10 North West 66
## 1785 2021-01-11 North West 79
## 1786 2021-01-12 North West 66
## 1787 2021-01-13 North West 85
## 1788 2021-01-14 North West 92
## 1789 2021-01-15 North West 87
## 1790 2021-01-16 North West 83
## 1791 2021-01-17 North West 81
## 1792 2021-01-18 North West 92
## 1793 2021-01-19 North West 92
## 1794 2021-01-20 North West 88
## 1795 2021-01-21 North West 85
## 1796 2021-01-22 North West 110
## 1797 2021-01-23 North West 103
## 1798 2021-01-24 North West 95
## 1799 2021-01-25 North West 86
## 1800 2021-01-26 North West 102
## 1801 2021-01-27 North West 104
## 1802 2021-01-28 North West 102
## 1803 2021-01-29 North West 99
## 1804 2021-01-30 North West 76
## 1805 2021-01-31 North West 84
## 1806 2021-02-01 North West 96
## 1807 2021-02-02 North West 82
## 1808 2021-02-03 North West 71
## 1809 2021-02-04 North West 79
## 1810 2021-02-05 North West 67
## 1811 2021-02-06 North West 62
## 1812 2021-02-07 North West 53
## 1813 2021-02-08 North West 73
## 1814 2021-02-09 North West 68
## 1815 2021-02-10 North West 71
## 1816 2021-02-11 North West 66
## 1817 2021-02-12 North West 67
## 1818 2021-02-13 North West 60
## 1819 2021-02-14 North West 50
## 1820 2021-02-15 North West 54
## 1821 2021-02-16 North West 52
## 1822 2021-02-17 North West 55
## 1823 2021-02-18 North West 51
## 1824 2021-02-19 North West 39
## 1825 2021-02-20 North West 29
## 1826 2021-02-21 North West 34
## 1827 2021-02-22 North West 25
## 1828 2021-02-23 North West 33
## 1829 2021-02-24 North West 33
## 1830 2021-02-25 North West 22
## 1831 2021-02-26 North West 37
## 1832 2021-02-27 North West 19
## 1833 2021-02-28 North West 25
## 1834 2021-03-01 North West 21
## 1835 2021-03-02 North West 1
## 1836 2020-03-01 South East 0
## 1837 2020-03-02 South East 0
## 1838 2020-03-03 South East 1
## 1839 2020-03-04 South East 0
## 1840 2020-03-05 South East 1
## 1841 2020-03-06 South East 0
## 1842 2020-03-07 South East 0
## 1843 2020-03-08 South East 1
## 1844 2020-03-09 South East 1
## 1845 2020-03-10 South East 1
## 1846 2020-03-11 South East 1
## 1847 2020-03-12 South East 0
## 1848 2020-03-13 South East 1
## 1849 2020-03-14 South East 1
## 1850 2020-03-15 South East 5
## 1851 2020-03-16 South East 8
## 1852 2020-03-17 South East 7
## 1853 2020-03-18 South East 10
## 1854 2020-03-19 South East 9
## 1855 2020-03-20 South East 13
## 1856 2020-03-21 South East 7
## 1857 2020-03-22 South East 25
## 1858 2020-03-23 South East 20
## 1859 2020-03-24 South East 22
## 1860 2020-03-25 South East 29
## 1861 2020-03-26 South East 35
## 1862 2020-03-27 South East 36
## 1863 2020-03-28 South East 36
## 1864 2020-03-29 South East 55
## 1865 2020-03-30 South East 58
## 1866 2020-03-31 South East 65
## 1867 2020-04-01 South East 66
## 1868 2020-04-02 South East 55
## 1869 2020-04-03 South East 72
## 1870 2020-04-04 South East 80
## 1871 2020-04-05 South East 82
## 1872 2020-04-06 South East 88
## 1873 2020-04-07 South East 100
## 1874 2020-04-08 South East 83
## 1875 2020-04-09 South East 104
## 1876 2020-04-10 South East 88
## 1877 2020-04-11 South East 88
## 1878 2020-04-12 South East 88
## 1879 2020-04-13 South East 84
## 1880 2020-04-14 South East 65
## 1881 2020-04-15 South East 72
## 1882 2020-04-16 South East 56
## 1883 2020-04-17 South East 86
## 1884 2020-04-18 South East 57
## 1885 2020-04-19 South East 70
## 1886 2020-04-20 South East 87
## 1887 2020-04-21 South East 51
## 1888 2020-04-22 South East 54
## 1889 2020-04-23 South East 57
## 1890 2020-04-24 South East 64
## 1891 2020-04-25 South East 51
## 1892 2020-04-26 South East 51
## 1893 2020-04-27 South East 41
## 1894 2020-04-28 South East 40
## 1895 2020-04-29 South East 47
## 1896 2020-04-30 South East 29
## 1897 2020-05-01 South East 37
## 1898 2020-05-02 South East 36
## 1899 2020-05-03 South East 17
## 1900 2020-05-04 South East 35
## 1901 2020-05-05 South East 29
## 1902 2020-05-06 South East 25
## 1903 2020-05-07 South East 27
## 1904 2020-05-08 South East 26
## 1905 2020-05-09 South East 28
## 1906 2020-05-10 South East 19
## 1907 2020-05-11 South East 25
## 1908 2020-05-12 South East 27
## 1909 2020-05-13 South East 18
## 1910 2020-05-14 South East 32
## 1911 2020-05-15 South East 25
## 1912 2020-05-16 South East 22
## 1913 2020-05-17 South East 18
## 1914 2020-05-18 South East 23
## 1915 2020-05-19 South East 12
## 1916 2020-05-20 South East 22
## 1917 2020-05-21 South East 15
## 1918 2020-05-22 South East 17
## 1919 2020-05-23 South East 21
## 1920 2020-05-24 South East 17
## 1921 2020-05-25 South East 13
## 1922 2020-05-26 South East 19
## 1923 2020-05-27 South East 19
## 1924 2020-05-28 South East 12
## 1925 2020-05-29 South East 22
## 1926 2020-05-30 South East 8
## 1927 2020-05-31 South East 12
## 1928 2020-06-01 South East 11
## 1929 2020-06-02 South East 13
## 1930 2020-06-03 South East 18
## 1931 2020-06-04 South East 11
## 1932 2020-06-05 South East 11
## 1933 2020-06-06 South East 10
## 1934 2020-06-07 South East 12
## 1935 2020-06-08 South East 8
## 1936 2020-06-09 South East 11
## 1937 2020-06-10 South East 11
## 1938 2020-06-11 South East 5
## 1939 2020-06-12 South East 6
## 1940 2020-06-13 South East 7
## 1941 2020-06-14 South East 7
## 1942 2020-06-15 South East 8
## 1943 2020-06-16 South East 14
## 1944 2020-06-17 South East 10
## 1945 2020-06-18 South East 4
## 1946 2020-06-19 South East 7
## 1947 2020-06-20 South East 5
## 1948 2020-06-21 South East 3
## 1949 2020-06-22 South East 2
## 1950 2020-06-23 South East 9
## 1951 2020-06-24 South East 7
## 1952 2020-06-25 South East 5
## 1953 2020-06-26 South East 8
## 1954 2020-06-27 South East 9
## 1955 2020-06-28 South East 6
## 1956 2020-06-29 South East 5
## 1957 2020-06-30 South East 5
## 1958 2020-07-01 South East 2
## 1959 2020-07-02 South East 8
## 1960 2020-07-03 South East 3
## 1961 2020-07-04 South East 6
## 1962 2020-07-05 South East 5
## 1963 2020-07-06 South East 4
## 1964 2020-07-07 South East 6
## 1965 2020-07-08 South East 3
## 1966 2020-07-09 South East 7
## 1967 2020-07-10 South East 3
## 1968 2020-07-11 South East 4
## 1969 2020-07-12 South East 5
## 1970 2020-07-13 South East 5
## 1971 2020-07-14 South East 5
## 1972 2020-07-15 South East 6
## 1973 2020-07-16 South East 3
## 1974 2020-07-17 South East 1
## 1975 2020-07-18 South East 5
## 1976 2020-07-19 South East 2
## 1977 2020-07-20 South East 6
## 1978 2020-07-21 South East 4
## 1979 2020-07-22 South East 2
## 1980 2020-07-23 South East 3
## 1981 2020-07-24 South East 1
## 1982 2020-07-25 South East 1
## 1983 2020-07-26 South East 3
## 1984 2020-07-27 South East 1
## 1985 2020-07-28 South East 3
## 1986 2020-07-29 South East 2
## 1987 2020-07-30 South East 3
## 1988 2020-07-31 South East 1
## 1989 2020-08-01 South East 2
## 1990 2020-08-02 South East 4
## 1991 2020-08-03 South East 0
## 1992 2020-08-04 South East 0
## 1993 2020-08-05 South East 0
## 1994 2020-08-06 South East 2
## 1995 2020-08-07 South East 0
## 1996 2020-08-08 South East 2
## 1997 2020-08-09 South East 0
## 1998 2020-08-10 South East 2
## 1999 2020-08-11 South East 1
## 2000 2020-08-12 South East 1
## 2001 2020-08-13 South East 0
## 2002 2020-08-14 South East 0
## 2003 2020-08-15 South East 2
## 2004 2020-08-16 South East 1
## 2005 2020-08-17 South East 0
## 2006 2020-08-18 South East 2
## 2007 2020-08-19 South East 1
## 2008 2020-08-20 South East 0
## 2009 2020-08-21 South East 0
## 2010 2020-08-22 South East 0
## 2011 2020-08-23 South East 1
## 2012 2020-08-24 South East 0
## 2013 2020-08-25 South East 1
## 2014 2020-08-26 South East 0
## 2015 2020-08-27 South East 1
## 2016 2020-08-28 South East 2
## 2017 2020-08-29 South East 1
## 2018 2020-08-30 South East 0
## 2019 2020-08-31 South East 2
## 2020 2020-09-01 South East 1
## 2021 2020-09-02 South East 1
## 2022 2020-09-03 South East 0
## 2023 2020-09-04 South East 1
## 2024 2020-09-05 South East 0
## 2025 2020-09-06 South East 1
## 2026 2020-09-07 South East 0
## 2027 2020-09-08 South East 0
## 2028 2020-09-09 South East 0
## 2029 2020-09-10 South East 1
## 2030 2020-09-11 South East 1
## 2031 2020-09-12 South East 0
## 2032 2020-09-13 South East 3
## 2033 2020-09-14 South East 1
## 2034 2020-09-15 South East 2
## 2035 2020-09-16 South East 2
## 2036 2020-09-17 South East 3
## 2037 2020-09-18 South East 1
## 2038 2020-09-19 South East 1
## 2039 2020-09-20 South East 0
## 2040 2020-09-21 South East 3
## 2041 2020-09-22 South East 0
## 2042 2020-09-23 South East 2
## 2043 2020-09-24 South East 1
## 2044 2020-09-25 South East 3
## 2045 2020-09-26 South East 2
## 2046 2020-09-27 South East 2
## 2047 2020-09-28 South East 6
## 2048 2020-09-29 South East 3
## 2049 2020-09-30 South East 4
## 2050 2020-10-01 South East 4
## 2051 2020-10-02 South East 2
## 2052 2020-10-03 South East 1
## 2053 2020-10-04 South East 1
## 2054 2020-10-05 South East 2
## 2055 2020-10-06 South East 1
## 2056 2020-10-07 South East 4
## 2057 2020-10-08 South East 1
## 2058 2020-10-09 South East 1
## 2059 2020-10-10 South East 3
## 2060 2020-10-11 South East 3
## 2061 2020-10-12 South East 4
## 2062 2020-10-13 South East 2
## 2063 2020-10-14 South East 2
## 2064 2020-10-15 South East 3
## 2065 2020-10-16 South East 2
## 2066 2020-10-17 South East 3
## 2067 2020-10-18 South East 4
## 2068 2020-10-19 South East 7
## 2069 2020-10-20 South East 8
## 2070 2020-10-21 South East 9
## 2071 2020-10-22 South East 5
## 2072 2020-10-23 South East 7
## 2073 2020-10-24 South East 5
## 2074 2020-10-25 South East 9
## 2075 2020-10-26 South East 13
## 2076 2020-10-27 South East 10
## 2077 2020-10-28 South East 10
## 2078 2020-10-29 South East 7
## 2079 2020-10-30 South East 6
## 2080 2020-10-31 South East 15
## 2081 2020-11-01 South East 18
## 2082 2020-11-02 South East 13
## 2083 2020-11-03 South East 16
## 2084 2020-11-04 South East 10
## 2085 2020-11-05 South East 10
## 2086 2020-11-06 South East 16
## 2087 2020-11-07 South East 17
## 2088 2020-11-08 South East 18
## 2089 2020-11-09 South East 19
## 2090 2020-11-10 South East 20
## 2091 2020-11-11 South East 20
## 2092 2020-11-12 South East 20
## 2093 2020-11-13 South East 12
## 2094 2020-11-14 South East 24
## 2095 2020-11-15 South East 25
## 2096 2020-11-16 South East 22
## 2097 2020-11-17 South East 23
## 2098 2020-11-18 South East 26
## 2099 2020-11-19 South East 21
## 2100 2020-11-20 South East 18
## 2101 2020-11-21 South East 23
## 2102 2020-11-22 South East 30
## 2103 2020-11-23 South East 29
## 2104 2020-11-24 South East 26
## 2105 2020-11-25 South East 42
## 2106 2020-11-26 South East 30
## 2107 2020-11-27 South East 31
## 2108 2020-11-28 South East 24
## 2109 2020-11-29 South East 37
## 2110 2020-11-30 South East 23
## 2111 2020-12-01 South East 29
## 2112 2020-12-02 South East 33
## 2113 2020-12-03 South East 36
## 2114 2020-12-04 South East 41
## 2115 2020-12-05 South East 36
## 2116 2020-12-06 South East 32
## 2117 2020-12-07 South East 25
## 2118 2020-12-08 South East 43
## 2119 2020-12-09 South East 44
## 2120 2020-12-10 South East 38
## 2121 2020-12-11 South East 48
## 2122 2020-12-12 South East 40
## 2123 2020-12-13 South East 41
## 2124 2020-12-14 South East 38
## 2125 2020-12-15 South East 51
## 2126 2020-12-16 South East 45
## 2127 2020-12-17 South East 54
## 2128 2020-12-18 South East 48
## 2129 2020-12-19 South East 43
## 2130 2020-12-20 South East 57
## 2131 2020-12-21 South East 66
## 2132 2020-12-22 South East 62
## 2133 2020-12-23 South East 70
## 2134 2020-12-24 South East 56
## 2135 2020-12-25 South East 71
## 2136 2020-12-26 South East 75
## 2137 2020-12-27 South East 77
## 2138 2020-12-28 South East 81
## 2139 2020-12-29 South East 78
## 2140 2020-12-30 South East 92
## 2141 2020-12-31 South East 93
## 2142 2021-01-01 South East 60
## 2143 2021-01-02 South East 95
## 2144 2021-01-03 South East 79
## 2145 2021-01-04 South East 106
## 2146 2021-01-05 South East 107
## 2147 2021-01-06 South East 121
## 2148 2021-01-07 South East 116
## 2149 2021-01-08 South East 125
## 2150 2021-01-09 South East 115
## 2151 2021-01-10 South East 126
## 2152 2021-01-11 South East 128
## 2153 2021-01-12 South East 170
## 2154 2021-01-13 South East 134
## 2155 2021-01-14 South East 140
## 2156 2021-01-15 South East 126
## 2157 2021-01-16 South East 154
## 2158 2021-01-17 South East 165
## 2159 2021-01-18 South East 151
## 2160 2021-01-19 South East 154
## 2161 2021-01-20 South East 134
## 2162 2021-01-21 South East 133
## 2163 2021-01-22 South East 129
## 2164 2021-01-23 South East 122
## 2165 2021-01-24 South East 116
## 2166 2021-01-25 South East 114
## 2167 2021-01-26 South East 130
## 2168 2021-01-27 South East 113
## 2169 2021-01-28 South East 128
## 2170 2021-01-29 South East 108
## 2171 2021-01-30 South East 93
## 2172 2021-01-31 South East 94
## 2173 2021-02-01 South East 95
## 2174 2021-02-02 South East 82
## 2175 2021-02-03 South East 95
## 2176 2021-02-04 South East 58
## 2177 2021-02-05 South East 68
## 2178 2021-02-06 South East 73
## 2179 2021-02-07 South East 63
## 2180 2021-02-08 South East 67
## 2181 2021-02-09 South East 37
## 2182 2021-02-10 South East 46
## 2183 2021-02-11 South East 62
## 2184 2021-02-12 South East 43
## 2185 2021-02-13 South East 34
## 2186 2021-02-14 South East 42
## 2187 2021-02-15 South East 48
## 2188 2021-02-16 South East 38
## 2189 2021-02-17 South East 35
## 2190 2021-02-18 South East 40
## 2191 2021-02-19 South East 39
## 2192 2021-02-20 South East 31
## 2193 2021-02-21 South East 35
## 2194 2021-02-22 South East 30
## 2195 2021-02-23 South East 29
## 2196 2021-02-24 South East 27
## 2197 2021-02-25 South East 23
## 2198 2021-02-26 South East 20
## 2199 2021-02-27 South East 22
## 2200 2021-02-28 South East 13
## 2201 2021-03-01 South East 10
## 2202 2021-03-02 South East 6
## 2203 2020-03-01 South West 0
## 2204 2020-03-02 South West 0
## 2205 2020-03-03 South West 0
## 2206 2020-03-04 South West 0
## 2207 2020-03-05 South West 0
## 2208 2020-03-06 South West 0
## 2209 2020-03-07 South West 0
## 2210 2020-03-08 South West 0
## 2211 2020-03-09 South West 0
## 2212 2020-03-10 South West 0
## 2213 2020-03-11 South West 1
## 2214 2020-03-12 South West 0
## 2215 2020-03-13 South West 0
## 2216 2020-03-14 South West 1
## 2217 2020-03-15 South West 0
## 2218 2020-03-16 South West 0
## 2219 2020-03-17 South West 2
## 2220 2020-03-18 South West 2
## 2221 2020-03-19 South West 4
## 2222 2020-03-20 South West 3
## 2223 2020-03-21 South West 6
## 2224 2020-03-22 South West 7
## 2225 2020-03-23 South West 8
## 2226 2020-03-24 South West 7
## 2227 2020-03-25 South West 9
## 2228 2020-03-26 South West 11
## 2229 2020-03-27 South West 13
## 2230 2020-03-28 South West 21
## 2231 2020-03-29 South West 18
## 2232 2020-03-30 South West 23
## 2233 2020-03-31 South West 23
## 2234 2020-04-01 South West 21
## 2235 2020-04-02 South West 23
## 2236 2020-04-03 South West 30
## 2237 2020-04-04 South West 42
## 2238 2020-04-05 South West 32
## 2239 2020-04-06 South West 34
## 2240 2020-04-07 South West 39
## 2241 2020-04-08 South West 47
## 2242 2020-04-09 South West 24
## 2243 2020-04-10 South West 46
## 2244 2020-04-11 South West 43
## 2245 2020-04-12 South West 23
## 2246 2020-04-13 South West 27
## 2247 2020-04-14 South West 24
## 2248 2020-04-15 South West 32
## 2249 2020-04-16 South West 29
## 2250 2020-04-17 South West 33
## 2251 2020-04-18 South West 25
## 2252 2020-04-19 South West 31
## 2253 2020-04-20 South West 26
## 2254 2020-04-21 South West 26
## 2255 2020-04-22 South West 23
## 2256 2020-04-23 South West 17
## 2257 2020-04-24 South West 19
## 2258 2020-04-25 South West 15
## 2259 2020-04-26 South West 27
## 2260 2020-04-27 South West 13
## 2261 2020-04-28 South West 17
## 2262 2020-04-29 South West 15
## 2263 2020-04-30 South West 26
## 2264 2020-05-01 South West 6
## 2265 2020-05-02 South West 7
## 2266 2020-05-03 South West 10
## 2267 2020-05-04 South West 17
## 2268 2020-05-05 South West 14
## 2269 2020-05-06 South West 19
## 2270 2020-05-07 South West 16
## 2271 2020-05-08 South West 6
## 2272 2020-05-09 South West 11
## 2273 2020-05-10 South West 5
## 2274 2020-05-11 South West 8
## 2275 2020-05-12 South West 7
## 2276 2020-05-13 South West 7
## 2277 2020-05-14 South West 6
## 2278 2020-05-15 South West 4
## 2279 2020-05-16 South West 4
## 2280 2020-05-17 South West 6
## 2281 2020-05-18 South West 4
## 2282 2020-05-19 South West 6
## 2283 2020-05-20 South West 1
## 2284 2020-05-21 South West 9
## 2285 2020-05-22 South West 7
## 2286 2020-05-23 South West 6
## 2287 2020-05-24 South West 3
## 2288 2020-05-25 South West 8
## 2289 2020-05-26 South West 11
## 2290 2020-05-27 South West 5
## 2291 2020-05-28 South West 10
## 2292 2020-05-29 South West 7
## 2293 2020-05-30 South West 3
## 2294 2020-05-31 South West 2
## 2295 2020-06-01 South West 7
## 2296 2020-06-02 South West 2
## 2297 2020-06-03 South West 7
## 2298 2020-06-04 South West 2
## 2299 2020-06-05 South West 2
## 2300 2020-06-06 South West 1
## 2301 2020-06-07 South West 3
## 2302 2020-06-08 South West 3
## 2303 2020-06-09 South West 0
## 2304 2020-06-10 South West 1
## 2305 2020-06-11 South West 2
## 2306 2020-06-12 South West 2
## 2307 2020-06-13 South West 2
## 2308 2020-06-14 South West 0
## 2309 2020-06-15 South West 2
## 2310 2020-06-16 South West 2
## 2311 2020-06-17 South West 0
## 2312 2020-06-18 South West 0
## 2313 2020-06-19 South West 0
## 2314 2020-06-20 South West 2
## 2315 2020-06-21 South West 0
## 2316 2020-06-22 South West 1
## 2317 2020-06-23 South West 1
## 2318 2020-06-24 South West 1
## 2319 2020-06-25 South West 0
## 2320 2020-06-26 South West 3
## 2321 2020-06-27 South West 0
## 2322 2020-06-28 South West 0
## 2323 2020-06-29 South West 1
## 2324 2020-06-30 South West 0
## 2325 2020-07-01 South West 0
## 2326 2020-07-02 South West 0
## 2327 2020-07-03 South West 0
## 2328 2020-07-04 South West 0
## 2329 2020-07-05 South West 1
## 2330 2020-07-06 South West 0
## 2331 2020-07-07 South West 0
## 2332 2020-07-08 South West 2
## 2333 2020-07-09 South West 0
## 2334 2020-07-10 South West 1
## 2335 2020-07-11 South West 0
## 2336 2020-07-12 South West 0
## 2337 2020-07-13 South West 1
## 2338 2020-07-14 South West 0
## 2339 2020-07-15 South West 0
## 2340 2020-07-16 South West 0
## 2341 2020-07-17 South West 1
## 2342 2020-07-18 South West 0
## 2343 2020-07-19 South West 0
## 2344 2020-07-20 South West 0
## 2345 2020-07-21 South West 0
## 2346 2020-07-22 South West 0
## 2347 2020-07-23 South West 0
## 2348 2020-07-24 South West 0
## 2349 2020-07-25 South West 0
## 2350 2020-07-26 South West 0
## 2351 2020-07-27 South West 0
## 2352 2020-07-28 South West 0
## 2353 2020-07-29 South West 0
## 2354 2020-07-30 South West 1
## 2355 2020-07-31 South West 0
## 2356 2020-08-01 South West 0
## 2357 2020-08-02 South West 0
## 2358 2020-08-03 South West 0
## 2359 2020-08-04 South West 0
## 2360 2020-08-05 South West 0
## 2361 2020-08-06 South West 0
## 2362 2020-08-07 South West 0
## 2363 2020-08-08 South West 0
## 2364 2020-08-09 South West 0
## 2365 2020-08-10 South West 0
## 2366 2020-08-11 South West 0
## 2367 2020-08-12 South West 0
## 2368 2020-08-13 South West 0
## 2369 2020-08-14 South West 1
## 2370 2020-08-15 South West 0
## 2371 2020-08-16 South West 0
## 2372 2020-08-17 South West 2
## 2373 2020-08-18 South West 0
## 2374 2020-08-19 South West 0
## 2375 2020-08-20 South West 0
## 2376 2020-08-21 South West 0
## 2377 2020-08-22 South West 0
## 2378 2020-08-23 South West 0
## 2379 2020-08-24 South West 0
## 2380 2020-08-25 South West 1
## 2381 2020-08-26 South West 0
## 2382 2020-08-27 South West 1
## 2383 2020-08-28 South West 0
## 2384 2020-08-29 South West 0
## 2385 2020-08-30 South West 0
## 2386 2020-08-31 South West 0
## 2387 2020-09-01 South West 0
## 2388 2020-09-02 South West 0
## 2389 2020-09-03 South West 0
## 2390 2020-09-04 South West 0
## 2391 2020-09-05 South West 0
## 2392 2020-09-06 South West 0
## 2393 2020-09-07 South West 0
## 2394 2020-09-08 South West 1
## 2395 2020-09-09 South West 0
## 2396 2020-09-10 South West 0
## 2397 2020-09-11 South West 0
## 2398 2020-09-12 South West 0
## 2399 2020-09-13 South West 1
## 2400 2020-09-14 South West 0
## 2401 2020-09-15 South West 0
## 2402 2020-09-16 South West 0
## 2403 2020-09-17 South West 1
## 2404 2020-09-18 South West 0
## 2405 2020-09-19 South West 0
## 2406 2020-09-20 South West 1
## 2407 2020-09-21 South West 0
## 2408 2020-09-22 South West 0
## 2409 2020-09-23 South West 0
## 2410 2020-09-24 South West 1
## 2411 2020-09-25 South West 0
## 2412 2020-09-26 South West 0
## 2413 2020-09-27 South West 0
## 2414 2020-09-28 South West 0
## 2415 2020-09-29 South West 0
## 2416 2020-09-30 South West 0
## 2417 2020-10-01 South West 0
## 2418 2020-10-02 South West 1
## 2419 2020-10-03 South West 0
## 2420 2020-10-04 South West 0
## 2421 2020-10-05 South West 0
## 2422 2020-10-06 South West 1
## 2423 2020-10-07 South West 0
## 2424 2020-10-08 South West 1
## 2425 2020-10-09 South West 1
## 2426 2020-10-10 South West 0
## 2427 2020-10-11 South West 4
## 2428 2020-10-12 South West 2
## 2429 2020-10-13 South West 0
## 2430 2020-10-14 South West 3
## 2431 2020-10-15 South West 1
## 2432 2020-10-16 South West 2
## 2433 2020-10-17 South West 8
## 2434 2020-10-18 South West 2
## 2435 2020-10-19 South West 2
## 2436 2020-10-20 South West 3
## 2437 2020-10-21 South West 6
## 2438 2020-10-22 South West 6
## 2439 2020-10-23 South West 5
## 2440 2020-10-24 South West 5
## 2441 2020-10-25 South West 5
## 2442 2020-10-26 South West 7
## 2443 2020-10-27 South West 6
## 2444 2020-10-28 South West 8
## 2445 2020-10-29 South West 11
## 2446 2020-10-30 South West 8
## 2447 2020-10-31 South West 4
## 2448 2020-11-01 South West 5
## 2449 2020-11-02 South West 11
## 2450 2020-11-03 South West 7
## 2451 2020-11-04 South West 8
## 2452 2020-11-05 South West 5
## 2453 2020-11-06 South West 11
## 2454 2020-11-07 South West 10
## 2455 2020-11-08 South West 10
## 2456 2020-11-09 South West 12
## 2457 2020-11-10 South West 6
## 2458 2020-11-11 South West 13
## 2459 2020-11-12 South West 17
## 2460 2020-11-13 South West 9
## 2461 2020-11-14 South West 8
## 2462 2020-11-15 South West 16
## 2463 2020-11-16 South West 18
## 2464 2020-11-17 South West 17
## 2465 2020-11-18 South West 26
## 2466 2020-11-19 South West 15
## 2467 2020-11-20 South West 25
## 2468 2020-11-21 South West 25
## 2469 2020-11-22 South West 24
## 2470 2020-11-23 South West 14
## 2471 2020-11-24 South West 20
## 2472 2020-11-25 South West 25
## 2473 2020-11-26 South West 16
## 2474 2020-11-27 South West 21
## 2475 2020-11-28 South West 35
## 2476 2020-11-29 South West 15
## 2477 2020-11-30 South West 22
## 2478 2020-12-01 South West 19
## 2479 2020-12-02 South West 15
## 2480 2020-12-03 South West 14
## 2481 2020-12-04 South West 20
## 2482 2020-12-05 South West 17
## 2483 2020-12-06 South West 13
## 2484 2020-12-07 South West 16
## 2485 2020-12-08 South West 19
## 2486 2020-12-09 South West 22
## 2487 2020-12-10 South West 21
## 2488 2020-12-11 South West 20
## 2489 2020-12-12 South West 15
## 2490 2020-12-13 South West 19
## 2491 2020-12-14 South West 20
## 2492 2020-12-15 South West 20
## 2493 2020-12-16 South West 9
## 2494 2020-12-17 South West 26
## 2495 2020-12-18 South West 11
## 2496 2020-12-19 South West 22
## 2497 2020-12-20 South West 19
## 2498 2020-12-21 South West 22
## 2499 2020-12-22 South West 11
## 2500 2020-12-23 South West 16
## 2501 2020-12-24 South West 18
## 2502 2020-12-25 South West 19
## 2503 2020-12-26 South West 24
## 2504 2020-12-27 South West 24
## 2505 2020-12-28 South West 21
## 2506 2020-12-29 South West 20
## 2507 2020-12-30 South West 17
## 2508 2020-12-31 South West 27
## 2509 2021-01-01 South West 29
## 2510 2021-01-02 South West 24
## 2511 2021-01-03 South West 28
## 2512 2021-01-04 South West 31
## 2513 2021-01-05 South West 31
## 2514 2021-01-06 South West 27
## 2515 2021-01-07 South West 30
## 2516 2021-01-08 South West 34
## 2517 2021-01-09 South West 26
## 2518 2021-01-10 South West 34
## 2519 2021-01-11 South West 40
## 2520 2021-01-12 South West 48
## 2521 2021-01-13 South West 40
## 2522 2021-01-14 South West 36
## 2523 2021-01-15 South West 46
## 2524 2021-01-16 South West 56
## 2525 2021-01-17 South West 35
## 2526 2021-01-18 South West 46
## 2527 2021-01-19 South West 45
## 2528 2021-01-20 South West 64
## 2529 2021-01-21 South West 59
## 2530 2021-01-22 South West 60
## 2531 2021-01-23 South West 54
## 2532 2021-01-24 South West 59
## 2533 2021-01-25 South West 59
## 2534 2021-01-26 South West 46
## 2535 2021-01-27 South West 45
## 2536 2021-01-28 South West 51
## 2537 2021-01-29 South West 42
## 2538 2021-01-30 South West 39
## 2539 2021-01-31 South West 36
## 2540 2021-02-01 South West 28
## 2541 2021-02-02 South West 36
## 2542 2021-02-03 South West 31
## 2543 2021-02-04 South West 32
## 2544 2021-02-05 South West 24
## 2545 2021-02-06 South West 38
## 2546 2021-02-07 South West 35
## 2547 2021-02-08 South West 30
## 2548 2021-02-09 South West 30
## 2549 2021-02-10 South West 17
## 2550 2021-02-11 South West 19
## 2551 2021-02-12 South West 26
## 2552 2021-02-13 South West 27
## 2553 2021-02-14 South West 16
## 2554 2021-02-15 South West 19
## 2555 2021-02-16 South West 10
## 2556 2021-02-17 South West 18
## 2557 2021-02-18 South West 19
## 2558 2021-02-19 South West 18
## 2559 2021-02-20 South West 12
## 2560 2021-02-21 South West 16
## 2561 2021-02-22 South West 10
## 2562 2021-02-23 South West 6
## 2563 2021-02-24 South West 9
## 2564 2021-02-25 South West 12
## 2565 2021-02-26 South West 6
## 2566 2021-02-27 South West 3
## 2567 2021-02-28 South West 9
## 2568 2021-03-01 South West 10
## 2569 2021-03-02 South West 21.5 Completion date
We extract the completion date from the NHS Pathways file timestamp:
The completion date of the NHS Pathways data is Wednesday 03 Mar 2021.
1.6 Auxiliary functions
These are functions which will be used further in the analyses.
Function to estimate the generalised R-squared as the proportion of deviance explained by a given model:
## Function to calculate R2 for Poisson model
## not adjusted for model complexity but all models have the same DF here
Rsq <- function(x) {
1 - (x$deviance / x$null.deviance)
}Function to extract growth rates per region as well as halving times, and the associated 95% confidence intervals:
## function to extract the coefficients, find the level of the intercept,
## reconstruct the values of r, get confidence intervals
get_r <- function(model) {
## extract coefficients and conf int
out <- data.frame(r = coef(model)) %>%
rownames_to_column("var") %>%
cbind(confint(model)) %>%
filter(!grepl("day_of_week", var)) %>%
filter(grepl("day", var)) %>%
rename(lower_95 = "2.5 %",
upper_95 = "97.5 %") %>%
mutate(var = sub("day:", "", var))
## reconstruct values: intercept + region-coefficient
for (i in 2:nrow(out)) {
out[i, -1] <- out[1, -1] + out[i, -1]
}
## find the name of the intercept, restore regions names
out <- out %>%
mutate(nhs_region = model$xlevels$nhs_region) %>%
select(nhs_region, everything(), -var)
## find halving times
halving <- log(0.5) / out[,-1] %>%
rename(halving_t = r,
halving_t_lower_95 = lower_95,
halving_t_upper_95 = upper_95)
## set halving times with exclusion intervals to NA
no_halving <- out$lower_95 < 0 & out$upper_95 > 0
halving[no_halving, ] <- NA_real_
## return all data
cbind(out, halving)
}Functions used in the correlation analysis between NHS Pathways reports and deaths:
## Function to calculate Pearson's correlation between deaths and lagged
## reports. Note that `pearson` can be replaced with `spearman` for rank
## correlation.
getcor <- function(x, ndx) {
return(cor(x$deaths[ndx],
x$note_lag[ndx],
use = "complete.obs",
method = "pearson"))
}
## Catch if sample size throws an error
getcor2 <- possibly(getcor, otherwise = NA)
getboot <- function(x) {
result <- boot::boot.ci(boot::boot(x, getcor2, R = 1000),
type = "bca")
return(data.frame(n = sum(!is.na(x$note_lag) & !is.na(x$deaths)),
r = result$t0,
r_low = result$bca[4],
r_hi = result$bca[5]))
}Function to classify the day of the week into weekend, Monday, and the rest:
## Fn to add day of week
day_of_week <- function(df) {
df %>%
dplyr::mutate(day_of_week = lubridate::wday(date, label = TRUE)) %>%
dplyr::mutate(day_of_week = dplyr::case_when(
day_of_week %in% c("Sat", "Sun") ~ "weekend",
day_of_week %in% c("Mon") ~ "monday",
!(day_of_week %in% c("Sat", "Sun", "Mon")) ~ "rest_of_week"
) %>%
factor(levels = c("rest_of_week", "monday", "weekend")))
}Custom color palettes, color scales, and vectors of colors:
2 Temporal trends in NHS Pathways reports
2.1 Outline
We look for temporal patterns in COVID-19 related 111/999 calls and 111 online reports. Analyses are broken down by NHS region. We also look for estimates of recent growth rate and associated doubling / halving time.
2.2 Reports by region over time
tab_date_region_all <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
dth %>%
mutate(trusted = case_when(date_report < max(dth$date_report)-delay_max ~ "Y",
date_report >= max(dth$date_report)-delay_max ~ "N"),
value = "Deaths",
vline = max(dth$date_report)-delay_max-1,
lab = "Truncated for reporting delay",
lab_pos_x = vline + 10,
lab_pos_y = 150,
lab_col = "darkgrey") %>%
rename(date = date_report,
n = deaths) %>%
bind_rows(
mutate(tab_date_region_all, value = "Reports",
trusted = "Y",
vline = as.Date("2020-03-23"),
lab = "Start of UK lockdown",
lab_pos_x = vline - 8,
lab_pos_y = 30200,
lab_col = "black")
) %>%
mutate(value = factor(value, levels = c("Reports","Deaths"))) -> dths_reports
plot_dth_report <-
ggplot(dths_reports, aes(date, n, colour = nhs_region)) +
# Add main points and lines, coloured by region and fade out deaths for excluded period
geom_point(aes(alpha = trusted)) +
geom_line(alpha = 0.2) +
geom_smooth(method = "loess", span = .5, color = "black") +
scale_colour_manual("", values = pal) +
scale_alpha_manual(values = c(0.3,1)) +
guides(alpha = F) +
# Add vertical markers for important dates with labels - different for each facet
ggnewscale::new_scale_colour() +
geom_vline(aes(xintercept = vline, col = value), lty = "solid") +
geom_text(aes(x = lab_pos_x, y = lab_pos_y, label = lab, col = value), size = 3) +
scale_colour_manual("",values = c("black","darkgrey"), guide = F) +
# Facet by deaths and reports
facet_grid(rows = vars(value), scales = "free_y", switch = "y") +
# Other formatting
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",strip.placement = "outside") +
rotate_x +
labs(x = NULL,
y = NULL)
plot_dth_report
2.3 Reports by region by age over time
We plot the number of 111/999 calls and 111 online reports by age, and the proportion of 111/999 calls and 111 online reports by age. In the second graph, the vertical lines indicate the proportion of individuals residing in the corresponding NHS region who belong to the corresponding age group.
tab_date_region_age_all <- x %>%
filter(!is.na(nhs_region),
age != "missing") %>%
group_by(date, nhs_region, age) %>%
summarise(n = sum(count))
tab_date_region_age_all %>%
ggplot(aes(x = date, y = n, fill = age)) +
geom_col(position = "stack") +
scale_fill_manual(values = age.pal) +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
axis.text.x = element_text(angle = 90, hjust = 1)) +
guides(fill = guide_legend(title = "Age", ncol = 3)) +
labs(x = NULL,
y = "Total daily reports by age") +
facet_wrap(~ nhs_region, ncol = 4)
tab_date_region_age_all <- tab_date_region_age_all %>%
group_by(date, nhs_region) %>%
summarise(tot = sum(n)) %>%
left_join(tab_date_region_age_all, by = c("date", "nhs_region")) %>%
mutate(prop_n = n/tot)
tab_date_region_age_all %>%
ggplot(aes(x = date, y = prop_n, color = age)) +
scale_color_manual(values = age.pal) +
geom_line() +
geom_point() +
geom_hline(data = nhs_region_pop, aes(yintercept = value, color = variable)) +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
axis.text.x = element_text(angle = 90, hjust = 1)) +
guides(color = guide_legend(title = "Age", ncol = 3)) +
labs(x = NULL,
y = "Proportion of daily reports by age") +
facet_wrap(~ nhs_region, ncol = 4)
2.4 Moving window model
We fit quasi-Poisson GLMs for 14-day windows to get growth rates over time.
## set moving time window (1/2/3 weeks)
w <- 14
# create empty df
r_all_sliding <- NULL
## make data for model
x_model_all_moving <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding <- bind_rows(r_all_sliding, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale,
w = 0.5)
#convert growth rates r to R0
r_all_sliding <- r_all_sliding %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))We examine the evolution of the growth rate by region over time.
# plot
plot_growth <-
r_all_sliding %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)") +
scale_colour_manual(values = pal)From the growth rate, we derive R and examine its value through time.
# plot
plot_R <-
r_all_sliding %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)") +
scale_colour_manual(values = pal)
R <- r_all_sliding %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
rotate_x +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
# strip.text.x = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "",
override.aes = list(fill = NA)),
fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))
2.5 Moving window model - stratified by age
We repeat the above analysis, where we fit quasi-Poisson GLMs for 14-day windows to get growth rates over time, but apply this to each age group separately (0-18, 19-69, 70-120 years old).
We first run the analysis for 0-18 years old.
## set moving time window (2 weeks)
w <- 14
# create empty df
r_all_sliding_0_18 <- NULL
## make data for model
x_model_all_moving_0_18 <- x %>%
filter(!is.na(nhs_region),
age == "0-18") %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving_0_18$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving_0_18 %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_0_18 <- bind_rows(r_all_sliding_0_18, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale, w = 0.5)
#convert growth rates r to R0
r_all_sliding_0_18 <- r_all_sliding_0_18 %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_0_18 %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "",override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)"
) +
scale_colour_manual(values = pal)# plot
plot_R <-
r_all_sliding_0_18 %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)"
) +
scale_colour_manual(values = pal)
R <- r_all_sliding_0_18 %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_0_18 %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
fig2_3_0_18 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))Then, we run the analysis for 19-69 years old.
## set moving time window (2 weeks)
w <- 14
# create empty df
r_all_sliding_19_69 <- NULL
## make data for model
x_model_all_moving_19_69 <- x %>%
filter(!is.na(nhs_region),
age == "19-69") %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving_19_69$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving_19_69 %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_19_69 <- bind_rows(r_all_sliding_19_69, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale, w = 0.5)
#convert growth rates r to R0
r_all_sliding_19_69 <- r_all_sliding_19_69 %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_19_69 %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)") +
scale_colour_manual(values = pal)# plot
plot_R <-
r_all_sliding_19_69 %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)"
) +
scale_colour_manual(values = pal)
R <- r_all_sliding_19_69 %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_19_69 %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
fig2_3_19_69 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))Finally, we run the analysis for 70-120 years old.
## set moving time window (2 weeks)
w <- 14
# create empty df
r_all_sliding_70_120 <- NULL
## make data for model
x_model_all_moving_70_120 <- x %>%
filter(!is.na(nhs_region),
age == "70-120") %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving_70_120$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving_70_120 %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_70_120 <- bind_rows(r_all_sliding_70_120, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale, w = 0.5)
#convert growth rates r to R0
r_all_sliding_70_120 <- r_all_sliding_70_120 %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_70_120 %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "",override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)"
) +
scale_colour_manual(values = pal)# plot
plot_R <-
r_all_sliding_70_120 %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)") +
scale_colour_manual(values = pal)
R <- r_all_sliding_70_120 %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_70_120 %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
fig2_3_70_120 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)"))) We combine the estimated growth rates and effective reproduction numbers into a single figure.
ggpubr::ggarrange(fig2_3_0_18,
fig2_3_19_69,
fig2_3_70_120,
nrow = 3,
labels = "AUTO",
common.legend = TRUE,
legend = "bottom",
align = "hv") 
3 Comparison with deaths time series
3.1 Outline
We want to explore the correlation between NHS Pathways reports and deaths, and assess the potential for reports to be used as an early warning system for disease resurgence.
Death data are publically available. We truncate the time series to avoid bias from reporting delay - we assume a conservative delay of three weeks.
3.2 Lagged correlation
We calculate Pearson’s correlation coefficient between deaths and NHS Pathways notifications using different lags. Confidence intervals are obtained using bootstrap. Note that results were also confirmed using Spearman’s rank correlation.
First we join the NHS Pathways and death data, and aggregate over all England:
## truncate death data for reporting delay
trunc_date <- max(dth$date_report) - delay_max
dth_trunc <- dth %>%
rename(date = date_report) %>%
filter(date <= trunc_date)
## join with notification data
all_data <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(count = sum(count, na.rm = T)) %>%
ungroup %>%
inner_join(dth_trunc,
by = c("date","nhs_region"))
all_tot <- all_data %>%
group_by(date) %>%
summarise(count = sum(count, na.rm = TRUE),
deaths = sum(deaths, na.rm = TRUE)) We calculate correlation with lagged NHS Pathways reports from 0 to 30 days behind deaths:
## Calculate all correlations + bootstrap CIs
lag_cor <- data.frame()
for (i in 0:30) {
## lag reports
summary <- all_tot %>%
mutate(note_lag = lag(count, i)) %>%
## calculate rank correlation and bootstrap CI
getboot(.) %>%
mutate(lag = i)
lag_cor <- bind_rows(lag_cor, summary)
}
cor_vs_lag <- ggplot(lag_cor, aes(lag, r)) +
theme_bw() +
geom_ribbon(aes(ymin = r_low, ymax = r_hi), alpha = 0.2) +
geom_hline(yintercept = 0, lty = "longdash") +
geom_point() +
geom_line() +
labs(x = "Lag between NHS pathways and death data (days)",
y = "Pearson's correlation") +
large_txt
cor_vs_lag
This analysis suggests that the best lag is 15 days. We then compare and plot the number of deaths reported against the number of NHS Pathways reports lagged by 15 days.
all_tot <- all_tot %>%
rename(date_death = date) %>%
mutate(note_lag = lag(count, lag_cor$lag[l_opt]),
note_lag_c = (note_lag - mean(note_lag, na.rm = T)),
date_note = lag(date_death,16))
lag_mod <- glm(deaths ~ note_lag, data = all_tot, family = "quasipoisson")
summary(lag_mod)
##
## Call:
## glm(formula = deaths ~ note_lag, family = "quasipoisson", data = all_tot)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -18.917 -16.212 -5.467 6.498 33.122
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.201e+00 6.745e-02 77.104 <2e-16 ***
## note_lag 1.157e-05 1.257e-06 9.207 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for quasipoisson family taken to be 225.0939)
##
## Null deviance: 80760 on 313 degrees of freedom
## Residual deviance: 66685 on 312 degrees of freedom
## (15 observations deleted due to missingness)
## AIC: NA
##
## Number of Fisher Scoring iterations: 5
exp(coefficients(lag_mod))
## (Intercept) note_lag
## 181.364747 1.000012
exp(confint(lag_mod))
## 2.5 % 97.5 %
## (Intercept) 158.514964 206.509829
## note_lag 1.000009 1.000014
Rsq(lag_mod)
## [1] 0.1742825
mod_fit <- as.data.frame(predict(lag_mod, type = "link", se.fit = TRUE)[1:2])
all_tot_pred <-
all_tot %>%
filter(!is.na(note_lag)) %>%
mutate(pred = mod_fit$fit,
pred.se = mod_fit$se.fit,
low = exp(pred - 1.96*pred.se),
hi = exp(pred + 1.96*pred.se))
glm_fit <- all_tot_pred %>%
filter(!is.na(note_lag)) %>%
ggplot(aes(x = note_lag, y = deaths)) +
geom_point() +
geom_line(aes(y = exp(pred))) +
geom_ribbon(aes(ymin = low, ymax = hi), alpha = 0.3, col = "grey") +
theme_bw() +
labs(y = "Daily number of\ndeaths reported",
x = "Daily number of NHS Pathways reports") +
large_txt
glm_fit
4 Supplementary figures
4.1 Serial interval distribution
This is a comparison of gamma versus lognormal distribution for the serial interval used to convert r to R in our analysis. Both distributions are parameterised with mean 4.7 and standard deviation 2.9.
SI_param <- epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale, w = 0.5)
SI_distribution2 <- distcrete::distcrete("lnorm", interval = 1,
meanlog = log(4.7),
sdlog = log(2.9), w = 0.5)
SI_dist1 <- data.frame(x = SI_distribution$r(1e5))
SI_dist1 <- count(SI_dist1, x) %>%
ggplot() +
geom_col(aes(x = x, y = n)) +
labs(x = "Serial interval (days)", y = "Frequency") +
scale_x_continuous(breaks = seq(0, 30, 5)) +
theme_bw()
SI_dist2 <- data.frame(x = SI_distribution2$r(1e5))
SI_dist2 <- count(SI_dist2, x) %>%
ggplot() +
geom_col(aes(x = x, y = n)) +
labs(x = "Serial interval (days)", y = "Frequency") +
scale_x_continuous(breaks = seq(0, 200, 20), limits = c(0, 200)) +
theme_bw()
ggpubr::ggarrange(SI_dist1,
SI_dist2,
nrow = 1,
labels = "AUTO") 
4.2 Sensitivity analysis - 7 or 21 days moving window
We reproduce the window analysis with either a 7 or 21 days window for sensitivity purposes.
First with the 7 days window:
## set moving time window (1/2/3 weeks)
w <- 7
# create empty df
r_all_sliding_7days <- NULL
## make data for model
x_model_all_moving <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_7days <- bind_rows(r_all_sliding_7days, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale,
w = 0.5)
#convert growth rates r to R0
r_all_sliding_7days <- r_all_sliding_7days %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_7days %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "",override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)") +
scale_colour_manual(values = pal)plot_R <- r_all_sliding_7days %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)") +
scale_colour_manual(values = pal)
R <- r_all_sliding_7days %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_7days %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
r_R_7 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))Then with the 21 days window:
## set moving time window (1/2/3 weeks)
w <- 21
# create empty df
r_all_sliding_21days <- NULL
## make data for model
x_model_all_moving <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_21days <- bind_rows(r_all_sliding_21days, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale,
w = 0.5)
#convert growth rates r to R0
r_all_sliding_21days <- r_all_sliding_21days %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_21days %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "",override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)") +
scale_colour_manual(values = pal)# plot
plot_R <-
r_all_sliding_21days %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)") +
scale_colour_manual(values = pal)
R <- r_all_sliding_21days %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_21days %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
r_R_21 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))And we combine both outputs into a single plot:
ggpubr::ggarrange(r_R_7,
r_R_21,
nrow = 2,
labels = "AUTO",
common.legend = TRUE,
legend = "bottom") 
4.3 Correlation between NHS Pathways reports and deaths by NHS region
lag_cor_reg <- data.frame()
for (i in 0:30) {
summary <-
all_data %>%
group_by(nhs_region) %>%
mutate(note_lag = lag(count, i)) %>%
## calculate rank correlation and bootstrap CI for each region
group_modify(~getboot(.x)) %>%
mutate(lag = i)
lag_cor_reg <- bind_rows(lag_cor_reg, summary)
}
cor_vs_lag_reg <-
lag_cor_reg %>%
ggplot(aes(lag, r, col = nhs_region)) +
geom_hline(yintercept = 0, lty = "longdash") +
geom_ribbon(aes(ymin = r_low, ymax = r_hi, col = NULL, fill = nhs_region), alpha = 0.2) +
geom_point() +
geom_line() +
facet_wrap(~nhs_region) +
scale_color_manual(values = pal) +
scale_fill_manual(values = pal, guide = F) +
theme_bw() +
labs(x = "Lag between NHS pathways and death data (days)", y = "Pearson's correlation", col = "NHS region") +
theme(legend.position = "bottom") +
guides(color = guide_legend(override.aes = list(fill = NA)))
cor_vs_lag_reg
5 Export data
We save the tables created during our analysis:
if (!dir.exists("excel_tables")) {
dir.create("excel_tables")
}
## list all tables, and loop over export
tables_to_export <- c("r_all_sliding", "lag_cor")
for (e in tables_to_export) {
rio::export(get(e),
file.path("excel_tables",
paste0(e, ".xlsx")))
}
## also export result from regression on lagged data
rio::export(lag_mod, file.path("excel_tables", "lag_mod.rds"))6 System information
6.1 Outline
The following information documents the system on which the document was compiled.
6.2 System
This provides information on the operating system.
Sys.info()
## sysname
## "Darwin"
## release
## "19.6.0"
## version
## "Darwin Kernel Version 19.6.0: Tue Jan 12 22:13:05 PST 2021; root:xnu-6153.141.16~1/RELEASE_X86_64"
## nodename
## "Mac-1614858062773.local"
## machine
## "x86_64"
## login
## "root"
## user
## "runner"
## effective_user
## "runner"6.3 R environment
This provides information on the version of R used:
6.4 R packages
This provides information on the packages used:
sessionInfo()
## R version 4.0.4 (2021-02-15)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Catalina 10.15.7
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] ggnewscale_0.4.5 ggpubr_0.4.0 lubridate_1.7.10
## [4] chngpt_2020.10-12 cyphr_1.1.0 DT_0.17
## [7] kableExtra_1.3.4 janitor_2.1.0 remotes_2.2.0
## [10] projections_0.5.2 earlyR_0.0.5 epitrix_0.2.2
## [13] distcrete_1.0.3 incidence_1.7.3 rio_0.5.26
## [16] reshape2_1.4.4 rvest_0.3.6 xml2_1.3.2
## [19] linelist_0.0.40.9000 forcats_0.5.1 stringr_1.4.0
## [22] dplyr_1.0.4 purrr_0.3.4 readr_1.4.0
## [25] tidyr_1.1.3 tibble_3.1.0 ggplot2_3.3.3
## [28] tidyverse_1.3.0 here_1.0.1 reportfactory_0.0.5
##
## loaded via a namespace (and not attached):
## [1] minqa_1.2.4 colorspace_2.0-0 selectr_0.4-2 ggsignif_0.6.1
## [5] ellipsis_0.3.1 rprojroot_2.0.2 snakecase_0.11.0 fs_1.5.0
## [9] rstudioapi_0.13 farver_2.1.0 fansi_0.4.2 splines_4.0.4
## [13] knitr_1.31 jsonlite_1.7.2 nloptr_1.2.2.2 broom_0.7.5
## [17] dbplyr_2.1.0 compiler_4.0.4 httr_1.4.2 backports_1.2.1
## [21] assertthat_0.2.1 Matrix_1.3-2 cli_2.3.1 htmltools_0.5.1.1
## [25] tools_4.0.4 gtable_0.3.0 glue_1.4.2 Rcpp_1.0.6
## [29] carData_3.0-4 cellranger_1.1.0 vctrs_0.3.6 svglite_2.0.0
## [33] nlme_3.1-152 matchmaker_0.1.1 crosstalk_1.1.1 xfun_0.21
## [37] ps_1.6.0 openxlsx_4.2.3 lme4_1.1-26 lifecycle_1.0.0
## [41] statmod_1.4.35 rstatix_0.7.0 MASS_7.3-53 scales_1.1.1
## [45] hms_1.0.0 parallel_4.0.4 sodium_1.1 yaml_2.2.1
## [49] curl_4.3 gridExtra_2.3 stringi_1.5.3 highr_0.8
## [53] kyotil_2020.10-12 boot_1.3-26 zip_2.1.1 rlang_0.4.10
## [57] pkgconfig_2.0.3 systemfonts_1.0.1 evaluate_0.14 lattice_0.20-41
## [61] labeling_0.4.2 htmlwidgets_1.5.3 cowplot_1.1.1 tidyselect_1.1.0
## [65] plyr_1.8.6 magrittr_2.0.1 R6_2.5.0 generics_0.1.0
## [69] DBI_1.1.1 mgcv_1.8-33 pillar_1.5.0 haven_2.3.1
## [73] foreign_0.8-81 withr_2.4.1 survival_3.2-7 abind_1.4-5
## [77] modelr_0.1.8 crayon_1.4.1 car_3.0-10 utf8_1.1.4
## [81] rmarkdown_2.7 viridis_0.5.1 grid_4.0.4 readxl_1.3.1
## [85] data.table_1.14.0 reprex_1.0.0 digest_0.6.27 webshot_0.5.2
## [89] munsell_0.5.0 viridisLite_0.3.0